@article{salomons_skulovich_ostfeld_2017, title={Battle of Water Networks DMAs: Multistage Design Approach}, volume={143}, ISSN={["1943-5452"]}, DOI={10.1061/(asce)wr.1943-5452.0000830}, abstractNote={AbstractLooped water distribution system (WDS) repartitioning to district metering areas (DMAs) gained popularity as an effective technique to manage the system and detect and reduce system leakage...}, number={10}, journal={JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT}, author={Salomons, Elad and Skulovich, Olya and Ostfeld, Avi}, year={2017}, month={Oct} }
 @article{berglund_areti_brill_mahinthakumar_2017, title={Successive linear approximation methods for leak detection in water distribution systems}, volume={143}, DOI={10.1061/(asce)wr.1943-5452.0000784}, abstractNote={AbstractIn many modern water networks, an emerging trend is to measure pressure at various points in the network for operational reasons. Because leaks typically induce a signature on pressure, the...}, number={8}, journal={Journal of Water Resources Planning and Management}, author={Berglund, A. and Areti, V. S. and Brill, D. and Mahinthakumar, G.}, year={2017} }
 @article{shafiee_berglund_berglund_brill_mahinthakumar_2016, title={Parallel Evolutionary Algorithm for Designing Water Distribution Networks to Minimize Background Leakage}, volume={142}, ISSN={0733-9496 1943-5452}, url={http://dx.doi.org/10.1061/(ASCE)WR.1943-5452.0000601}, DOI={10.1061/(asce)wr.1943-5452.0000601}, abstractNote={AbstractLeaks in water distribution systems waste energy and water resources, increase damage to infrastructure, and may allow contamination of potable water. This research develops an evolutionary algorithm-based approach to minimize the cost of water loss, new infrastructure, and operations that reduce background leakage. A new design approach is introduced that minimizes capital and operational costs, including energy and water loss costs. Design decisions identify a combination of infrastructure improvements, including pipe replacement and valve installment, and operation rules for tanks and pumps. Solution approaches are developed to solve both a single-objective and multiobjective problem formulation. A genetic algorithm and a nondominated sorting genetic algorithm are implemented within a high-performance computing platform to select tank sizes, pump placement and operations, placement of pressure-reducing valves, and pipe diameters for replacing pipes. The evolutionary algorithm approaches identif...}, number={5}, journal={Journal of Water Resources Planning and Management}, publisher={American Society of Civil Engineers (ASCE)}, author={Shafiee, M. Ehsan and Berglund, Andrew and Berglund, Emily Zechman and Brill, E. Downey, Jr. and Mahinthakumar, G.}, year={2016}, month={May} }
 @article{wang_brill_ranjithan_sankarasubramanian_2015, title={A framework for incorporating ecological releases in single reservoir operation}, volume={78}, ISSN={0309-1708}, url={http://dx.doi.org/10.1016/j.advwatres.2015.01.006}, DOI={10.1016/j.advwatres.2015.01.006}, abstractNote={Most reservoir operation practices consider downstream environmental flow as a constraint to meet a minimum release. The resulting flow regime may not necessarily provide downstream aquatic conditions to support healthy ecosystems. These effects can be quantified in terms of changes in values of parameters that represent the flow regimes. Numerous studies have focused on determining the ecological response to hydrological alteration caused by reservoir operation. To mitigate hydrological alteration and restore the natural flow regime as much as possible, a reservoir operation framework is proposed to explicitly incorporate ecological flow requirements. A general optimization-based decision model is presented to consider simultaneously the multiple anthropogenic uses of the reservoir and desirable ecological releases represented by parameters that capture the flow regime. Multiple uses of the reservoir, including water supply, hydropower generation, etc., are modeled as a mixed integer programming problem. Hydropower generation, which is represented by a nonlinear function that usually depends on head and water flow, is linearized using a two-dimensional function. Investigations using a reservoir in Virginia, located in the southeastern United States, demonstrate that compared to standard releases based on current operation practice, releases simulated using this framework perform better in mimicking pre-development flows. The tradeoff between anthropogenic use and ecological releases is investigated. The framework is first demonstrated for instances with perfect stream flow information. To examine the flexibility of this framework in reservoir release management, monthly flow forecasts and disaggregated daily flow conditions are incorporated. Retrospective monthly flow forecasts are obtained through regression models that use gridded precipitation forecasts and gridded soil moisture estimates as predictors. A nonparametric method is chosen to disaggregate monthly flow forecasts to daily flow conditions. Compared with daily flow climatology, forecasted monthly and daily flow better preserves flow variability and result in lower changes of flow parameters under the proposed framework.}, journal={Advances in Water Resources}, publisher={Elsevier BV}, author={Wang, Hui and Brill, Earl D. and Ranjithan, Ranji S. and Sankarasubramanian, A.}, year={2015}, month={Apr}, pages={9–21} }
 @article{marchi_salomons_ostfeld_kapelan_simpson_zecchin_maier_wu_elsayed_song_et al._2014, edition={+59 co-authors}, title={Battle of the Water Networks II}, volume={140}, ISSN={0733-9496 1943-5452}, url={http://dx.doi.org/10.1061/(ASCE)WR.1943-5452.0000378}, DOI={10.1061/(ASCE)WR.1943-5452.0000378}, abstractNote={The Battle of the Water Networks II (BWN-II) is the latest of a series of competitions related to the design and operation of water distribution systems (WDSs) undertaken within the Water Distribution Systems Analysis (WDSA) Symposium series. The BWN-II problem specification involved a broadly defined design and operation problem for an existing network that has to be upgraded for increased future demands, and the addition of a new development area. The design decisions involved addition of new and parallel pipes, storage, operational controls for pumps and valves, and sizing of backup power supply. Design criteria involved hydraulic, water quality, reliability, and environmental performance measures. Fourteen teams participated in the Battle and presented their results at the 14th Water Distribution Systems Analysis conference in Adelaide, Australia, September 2012. This paper summarizes the approaches used by the participants and the results they obtained. Given the complexity of the BWN-II problem and the innovative methods required to deal with the multiobjective, high dimensional and computationally demanding nature of the problem, this paper represents a snap-shot of state of the art methods for the design and operation of water distribution systems. A general finding of this paper is that there is benefit in using a combination of heuristic engineering experience and sophisticated optimization algorithms when tackling complex real-world water distribution system design problems. (C) 2014 American Society of Civil Engineers.}, number={7}, journal={Journal of Water Resources Planning and Management}, publisher={American Society of Civil Engineers (ASCE)}, author={Marchi, Angela and Salomons, Elad and Ostfeld, Avi and Kapelan, Zoran and Simpson, Angus R. and Zecchin, Aaron C. and Maier, Holger R. and Wu, Zheng Yi and Elsayed, Samir M. and Song, Yuan and et al.}, year={2014}, month={Jul}, pages={04014009} }
 @article{shafiee_berglund_berglund_brill_mahinthakumar_2014, title={Evolutionary Computation-based Decision-making Framework for Designing Water Networks to Minimize Background Leakage}, volume={89}, ISSN={1877-7058}, url={http://dx.doi.org/10.1016/J.PROENG.2014.11.167}, DOI={10.1016/J.PROENG.2014.11.167}, abstractNote={Abstract This research minimizes the impact of leaks on the operation of the system to reduce lost water while meeting typical management goals. A genetic algorithm approach is implemented within a high-performance computing platform to select tank sizes, pump placement and operations, placement of pressure control valves, and pipe diameters for replacing pipes. It identifies solutions that minimize water loss, operational costs, and capital costs, while maintaining pressure at nodes and operational feasibility for tanks. Multiple problem formulations are solved that use alternative objective functions and allow varying degrees of freedom in the decision space. The methodology is demonstrated to identify a water distribution system re-design for the C-Town case study.}, journal={Procedia Engineering}, publisher={Elsevier BV}, author={Shafiee, M.E. and Berglund, A. and Berglund, E. Zechman and Brill, E. Downey, Jr. and Mahinthakumar, G.}, year={2014}, pages={118–125} }
 @article{li_sankarasubramanian_ranjithan_brill_2014, title={Improved regional water management utilizing climate forecasts: An interbasin transfer model with a risk management framework}, volume={50}, ISSN={0043-1397}, url={http://dx.doi.org/10.1002/2013WR015248}, DOI={10.1002/2013wr015248}, abstractNote={Abstract}, number={8}, journal={Water Resources Research}, publisher={American Geophysical Union (AGU)}, author={Li, Weihua and Sankarasubramanian, A. and Ranjithan, R. S. and Brill, E. D.}, year={2014}, month={Aug}, pages={6810–6827} }
 @inproceedings{jasper_mahinthakumar_ranjithan_brill_2013, title={A Sensitivity Analysis of Data Measurement Types for Leak Detection in Water Distribution Systems}, ISBN={9780784412947}, url={http://dx.doi.org/10.1061/9780784412947.059}, DOI={10.1061/9780784412947.059}, abstractNote={It is estimated that 15-40% of water is unaccounted for in urban water systems. This is mostly caused by small leaks, which are difficult to locate. Routinely measured pressure, flow, and water quality data can be used to locate leaks in the water network using an inverse modeling approach. For a known sensor configuration, the leak locations can be found by minimizing the difference between real and simulated measurements. However, when comparing measurement types (pressure, flow, or quality), some may be more sensitive to leak location than others. Furthermore, some measurement types may be more or less sensitive depending on the leak magnitude or the proximity of the leak to the sensors. The measurements types that are more sensitive to location will have a stronger signature and would need to be weighted more in an inverse modeling approach, especially in the presence of noise. Preliminary research suggests that water quality measurements are more sensitive to leak location when a leak is small, and that flow measurements are more sensitive when a leak is large. In this research, a series of sensitivity analyses are conducted on different networks to investigate the sensitivity of these measurements with respect to leak location, magnitude, and proximity of sensors to the leak location. 1. Motivation Water distribution systems are a vital part of modern infrastructure, yet they are susceptible to leaks and contaminant intrusion. High pressure, freezing water, or aging can cause cracks in the distribution pipes that lead to small, gradual leaks into the ground that are difficult to detect. In some aging systems, up to 40% of water is lost to leaks [1]. Utilities typically monitor locations that are prone to leak, based on a history of previous leaks or the age of the pipes. A leak can be detected, for example, by using acoustic listening devices that pick up on the sound of water escaping from the pipe, among other methods. However, it is expensive and time intensive to manually check the suspected pipes. There are routinely collected measurements of pressure, flow, and water quality at sensor locations. These measurements can carry a signature that will help identify the leak location and}, booktitle={World Environmental and Water Resources Congress 2013}, publisher={American Society of Civil Engineers}, author={Jasper, Micah N. and Mahinthakumar, Gnanamanikam (Kumar) and Ranjithan, Sanmugavadivel (Ranji) and Brill, Earl Downey}, year={2013}, month={May} }
 @inproceedings{jasper_mahinthakumar_ranjithan_brill_2013, title={Leak Detection in Water Distribution Systems Using the Dividing Rectangles (DIRECT) Search}, ISBN={9780784412947}, url={http://dx.doi.org/10.1061/9780784412947.078}, DOI={10.1061/9780784412947.078}, abstractNote={Leak detection and management is an important problem in water distribution systems since it has been documented that up to 40% of the water may be lost to leaks in many aging systems. Small gradual leaks, which represent more than half of all leaks, are difficult to locate. Routinely measured pressure, flow, and water quality data in combination with a simulation-optimization inverse modeling approach could be used to characterize leakage. In this approach, the leak locations are found by minimizing the difference between real and simulated measurements for a known sensor configuration. Simulation-optimization approaches are computationally demanding because millions of simulations of a network simulator (e.g., EPANET) may be required to achieve a satisfactory solution. This problem is alleviated using a high performance computing (HPC) framework that enables many parallel simulations of the water system using EPANET. This research is modifying an existing global search algorithm, called the Dividing Rectangles (DIRECT) Search that is traditionally used for continuous functions, to enable parallel simulations and a mix of discrete variables (for leak locations) and continuous variables (for leak magnitudes). The modified algorithm is being tested with traditional continuous test functions, discrete test functions, and test water distribution networks. 1. Motivation Water distribution systems are a vital part of modern infrastructure, yet they are susceptible to leaks and contaminant intrusion. High pressure, freezing water, or aging can cause cracks in the distribution pipes that lead to small, gradual leaks into the ground that are difficult to detect. In some aging systems, up to 40% of water is lost to leaks [1]. Utilities typically monitor locations that are prone to leak, based on a history of previous leaks or the age of the pipes. A leak can be detected, for example, by using acoustic listening devices that pick up on the sound of water escaping from the pipe, among other methods. However, it is expensive and time intensive to manually check the suspected pipes. There are routinely collected measurements of pressure, flow, and water quality at sensor locations. These measurements can carry a signature that will help identify the leak location and}, booktitle={World Environmental and Water Resources Congress 2013}, publisher={American Society of Civil Engineers}, author={Jasper, Micah N. and Mahinthakumar, Gnanamanikam (Kumar) and Ranjithan, Sanmugavadivel (Ranji) and Brill, Earl Downey}, year={2013}, month={May} }
 @article{kumar_brill_mahinthakumar_ranjithan_2012, title={Contaminant source characterization in water distribution systems using binary signals}, volume={14}, ISSN={1464-7141 1465-1734}, url={http://dx.doi.org/10.2166/hydro.2012.073}, DOI={10.2166/hydro.2012.073}, abstractNote={This paper presents a simulation–optimization-based method for identification of contamination source characteristics in a water distribution system using filtered data from threshold-based binary water quality signals. The effects of quality and quantity of the data on the accuracy of the source identification methodology are investigated. This study also addresses the issue of non-uniqueness in contaminant source identification under various data availability conditions. To establish the robustness and applicability of the methodology, numerous scenarios are investigated for a wide range of contamination incidents associated with two different networks. Results indicate that, even though use of lower resolution sensors lead to more non-unique solutions, the true source location is always included among these solutions.}, number={3}, journal={Journal of Hydroinformatics}, publisher={IWA Publishing}, author={Kumar, Jitendra and Brill, E. Downey and Mahinthakumar, G. and Ranjithan, S. Ranji}, year={2012}, month={Jul}, pages={585–602} }
 @inproceedings{sreepathi_brill_ranjithan_mahinthakumar_2012, title={Parallel Multi-Swarm Optimization Framework for Search Problems in Water Distribution Systems}, ISBN={9780784412312}, url={http://dx.doi.org/10.1061/9780784412312.323}, DOI={10.1061/9780784412312.323}, abstractNote={Population based heuristic search methods such as evolutionary algorithms (EA) and particle swarm optimization (PSO) methods are widely used for solving optimization problems especially when classical techniques are inadequate. A parallel optimization framework using multiple concurrent particle swarms is developed and applied to water distribution problems. Details of the enabling framework that couples the optimization methods with a parallel simulator built around EPANET will be discussed. In addition, algorithmic and computational performance results using ORNL’s and ANL’s leadership class parallel architectures will be presented for leakage detection and contaminant source characterization problems for two water distribution networks with 1,834 and 12,457 nodes respectively.}, booktitle={World Environmental and Water Resources Congress 2012}, publisher={American Society of Civil Engineers}, author={Sreepathi, Sarat and Brill, Downey and Ranjithan, Ranji and Mahinthakumar, Gnanamanikam (Kumar)}, year={2012}, month={May} }
 @inproceedings{barandouzi_mahinthakumar_ranjithan_brill_2012, title={Probabilistic Mapping of Water Leakage Characterizations Using a Bayesian Approach}, ISBN={9780784412312}, url={http://dx.doi.org/10.1061/9780784412312.326}, DOI={10.1061/9780784412312.326}, abstractNote={Water Distribution Systems are one of the most substantial and vulnerable part of civil infrastructure systems. For the reason that many large water distribution systems are old, which results in more leakage and expenses (e.g., increasing pump head, pipe burst, constituents’ replacement), a significant portion of water produced by the utilities never passes through the consumers’ meters. Due to the complex nature and vast spatial extent of a water distribution system it may be difficult for the utility personnel to identify and fix the leaks, therefore it is imperative to develop software frameworks for modeling and analyzing leakage in water distribution system during ordinary operational conditions as well as unexpected events. In this paper a Bayesian approach with Markov chain Monte Carlo method is implemented to map probabilistic characterizations of water leakage. If for this purpose physical parameters such as pipe vintage, material, and loading are available, they can be are used to develop prior information; otherwise, a uniform prior may be assumed. Routinely measured water quality, pressure, and flow measurements together with the uncertainty in demand are used to develop the likelihood function. The analyses are facilitated through the EPANET water distribution simulation tool. The efficiency and versatility of the proposed methodology is examined using water distribution network.}, booktitle={World Environmental and Water Resources Congress 2012}, publisher={American Society of Civil Engineers}, author={Barandouzi, M. A. and Mahinthakumar, G. and Ranjithan, R. and Brill, E. D.}, year={2012}, month={May} }
 @inproceedings{kumar_sreepathi_brill_ranjithan_mahinthakumar_2010, title={Detection of Leaks in Water Distribution System Using Routine Water Quality Measurements}, ISBN={9780784411148}, url={http://dx.doi.org/10.1061/41114(371)426}, DOI={10.1061/41114(371)426}, abstractNote={Water distributions systems are primary means of safe drinking water supply to the public. Water produced and delivered to the distribution system is intended for the customer. However, a significant amount of the water is lost in the distribution system before even reaching the customers. Water customers are metered for the usage at end connection but a significant portion of water produced by the utilities never passes through the meters. This leads to wastage of valuable water and loss of revenues for the utilities. The occurrence of leaks depends on the factors like material, composition, age and joining methods of the distribution systems components. Due to the complex nature and vast spatial extent of a water distribution system it may be difficult for the utility personnel to identify and fix the leaks. Traditionally, the method of inverse transient analysis (ITA) has been used by the researchers for identifying the leaks in a distribution system. While transient analysis is an efficient method for leak detection, it often requires that a series of hydraulic transients (or pressure pulses) be injected into the system in order to detect the leaks (e.g., controlled opening/closing of a fire hydrant). In contrast to ITA, this work attempts to use routinely measured water quality and pressure measurements for the detection of leaks. Distribution systems are routinely monitored for several water quality parameters such as Chlorine, pH, and turbidity. Water loss due to any leaks present in the system would impact the flow characteristics of the system and would have an impact on the water quality. In this study a methodology has been developed to use the water quality data along with available pressure measurements for the improved detection of leaks in a water distribution system. Leak detection is formulated as an inverse problem and solved using a simulation-optimization approach.}, booktitle={World Environmental and Water Resources Congress 2010}, publisher={American Society of Civil Engineers}, author={Kumar, Jitendra and Sreepathi, Sarat and Brill, E. Downey and Ranjithan, Ranji and Mahinthakumar, G.}, year={2010}, month={May} }
 @inproceedings{kumar_brill_mahinthakumar_ranjithan_2010, title={Identification of Reactive Contaminant Sources in a Water Distribution System under the Conditions of Data Uncertainties}, ISBN={9780784411148}, url={http://dx.doi.org/10.1061/41114(371)442}, DOI={10.1061/41114(371)442}, abstractNote={Water distribution systems are designed for fast and efficient transport of the drinking water and mixing of chlorine to maintain the required disinfectant levels in the system. Thus, any contaminant if injected in the system would also spread quickly through the network and can have serious impact on public health if consumed. Contaminant injected during any intentional contamination event can be chemical or biological, the nature of which may remain unknown. Practically it's not possible to monitor any system for the presence of all possible chemical or biological contaminants. However, the distribution systems are routinely monitored for several water quality parameters like chlorine, pH, etc. Any contaminant injected in the system would react with water and chlorine leading to the increased degradation of the chlorine levels in the system. In our past work we developed methodology to use routine chlorine measurements as a surrogate to identify a contamination event in a WDS. An evolutionary algorithm based approach simulation-optimization was developed to identify the contaminant source characteristics (i.e., location of the contaminant source, time of start of injection and injection pattern) during a contamination event under conditions of uncertainty about the reaction kinetics of the contaminant in the system. The investigation was extended to study the source characterization problem under different uncertain reaction conditions. We present here a detailed analysis of source characterization problem for the reactive contaminants and the simulation-optimization methodology developed. Case studies carried out on a number of water distributions systems will be reported.}, booktitle={World Environmental and Water Resources Congress 2010}, publisher={American Society of Civil Engineers}, author={Kumar, Jitendra and Brill, E. Downey and Mahinthakumar, G. and Ranjithan, Ranji}, year={2010}, month={May} }
 @article{reichold_zechman_brill_holmes_2010, title={Simulation-Optimization Framework to Support Sustainable Watershed Development by Mimicking the Predevelopment Flow Regime}, volume={136}, ISSN={0733-9496 1943-5452}, url={http://dx.doi.org/10.1061/(asce)wr.1943-5452.0000040}, DOI={10.1061/(asce)wr.1943-5452.0000040}, abstractNote={A new approach is presented to achieve a more aggressive sustainability objective for designing transportation infrastructure and land use planning: to design BMPs to continuously mimic the natural flow regime and ensure that ecosystems downstream of development would not be adversely affected. As the land uses are changed for development of urban areas and transportation infrastructure, ecosystems in receiving water bodies are significantly affected by the changes in duration, peak, and minimum flows. Though Best Management Practices (BMPs) are typically designed to not exceed some peak flow during a design storm and perhaps maintain a minimum flow at low-flow periods, downstream conditions are altered, potentially harming ecosystems. A new approach is presented to achieve a more aggressive sustainability objective: to design BMPs to continuously mimic the natural flow regime and ensure that ecosystems downstream of development would not be adversely affected. This objective may not be achievable through the implementation of a single detention pond at a watershed outlet; a system of BMPs strategically placed throughout the watershed may be required. Several BMPs exist as options for treatment, such as detention/retention ponds, constructed wetland systems, infiltration systems (i.e., porous pavement), and vegetative filtrations systems. As each system chosen for implementation must be specified by a set of design decisions and placement location, an efficient mechanism of optimization is needed to handle the large array of decisions. In addition, a comprehensive modeling framework is needed to simulate a collection of BMPs simultaneously. A quantitative analysis framework is described and illustrated for coupling BMP and watershed models with optimization techniques.}, number={3}, journal={Journal of Water Resources Planning and Management}, publisher={American Society of Civil Engineers (ASCE)}, author={Reichold, Laurel and Zechman, Emily M. and Brill, E. Downey and Holmes, Hillary}, year={2010}, month={May}, pages={366–375} }
 @inproceedings{liu_brill_mahinthakumar_ranjithan_2009, title={A Hybrid Heuristic Search Approach for Contaminant Source Characterization}, ISBN={9780784410363}, url={http://dx.doi.org/10.1061/41036(342)63}, DOI={10.1061/41036(342)63}, abstractNote={The rapid discovery of the contaminant source and its mass loading characteristics in a water distribution system (WDS) is vital for generating an efficient control strategy during a contamination event. Previous work on the Adaptive Dynamic Optimization Technique (ADOPT), which was developed as an Evolution Strategy (ES) based procedure, presents an approach to estimate the source characteristics adaptively, given dynamically updated observation data. Although this simulation-optimization approach is promising, it is computationally expensive, which poses challenges in the context of real-time solutions. This paper reports the findings of an investigation that builds upon the prior work by introducing a hybrid heuristic search method for the real-time characterization of a contaminant source. This new method integrates the ES-based ADOPT with a logistic regression (LR) analysis and a local improvement method to expedite the convergence and possibly solve the problem quickly. As a prescreening technique, a LR analysis step is performed prior to ADOPT; this step reduces the search space by eliminating unnecessary source nodes as potential source locations. Then, a local search (LS) approach is embedded into some of the algorithmic steps in ADOPT to serve as a postscreening step that potentially speeds up the convergence in localized regions in the solution space. Numerical experiments for the proposed hybrid approach are performed on an example water distribution network, and the results are compared with those of the standard implementation of ADOPT.}, booktitle={World Environmental and Water Resources Congress 2009}, publisher={American Society of Civil Engineers}, author={Liu, Li and Brill, E. Downey and Mahinthakumar, G. (Kumar) and Ranjithan, S. Ranji}, year={2009}, month={May} }
 @inproceedings{kumar_brill_mahinthakumar_ranjithan_2009, title={Characterizing Reactive Contaminant Sources in a Water Distribution System}, ISBN={9780784410363}, url={http://dx.doi.org/10.1061/41036(342)65}, DOI={10.1061/41036(342)65}, abstractNote={Accurate knowledge of the characteristics of the contamination source during a contamination event is necessary for development of any mitigation and control strategy. Contaminant injected in a system is most likely to be reactive with chlorine; however, it is impractical for water quality monitoring systems to be able to monitor for the presence of all possible contaminants. In any distribution system, chlorine levels and other water quality parameters (pH, conductance, etc.) are routinely monitored to maintain the prescribed disinfection capacity. Any reactive contaminant would affect the chlorine levels resulting in deviations in the expected chlorine levels from those expected under normal operating conditions. Anomalies in the chlorine concentration from that of the expected value can be used as a surrogate to characterize the contaminant source in the system. In the absence of knowing the reactive characteristics of the contaminants, the location of injection, and injection pattern, source identification becomes a difficult problem to solve. Source identification can be posed as an inverse problem. In earlier work authors investigated the effect of the order of reaction kinetics of the contaminant with chlorine and its impact on source identification problem assuming the reaction kinetics to be known. That work is extended to investigate a methodology to address the source identification problem based on chlorine measurements, and the effects of different uncertain contamination conditions. Findings from a range of scenarios will be presented and discussed.}, booktitle={World Environmental and Water Resources Congress 2009}, publisher={American Society of Civil Engineers}, author={Kumar, Jitendra and Brill, E. Downey and Mahinthakumar, G and Ranjithan, Ranji}, year={2009}, month={May} }
 @inproceedings{liu_zechman_brill, jr._mahinthakumar_ranjithan_uber_2008, title={Adaptive Contamination Source Identification in Water Distribution Systems Using an Evolutionary Algorithm-based Dynamic Optimization Procedure}, ISBN={9780784409411}, url={http://dx.doi.org/10.1061/40941(247)123}, DOI={10.1061/40941(247)123}, abstractNote={Accidental drinking water contamination has long been and remains a major threat to water security throughout the world. Consequently, contamination source identification is an important and difficult problem in the managing safety in water distribution systems. This problem involves the characterization of the contaminant source based on observations that are streaming from a set of sensors in the distribution network. Since contamination spread in a water distribution network is relatively quick and unpredictable, rapid identification of the source location and related characteristics is important to take contaminant control and containment actions. As the contaminant event unfolds, the streaming data could be processed over time to adaptively estimate the source characteristics. This provides an estimate of the source characteristics at any time after a contamination event is detected, and this estimate is continually updated as new observations become available. We pose and solve this problem using a dynamic optimization procedure that could potentially provide a real-time response. As time progresses, additional data is observed at a set of sensors, changing the vector of observations that should be predicted. Thus, the prediction error function is updated dynamically, changing the objective function in the optimization model. We investigate a new multi population-based search using an evolutionary algorithm (EA) that at any time represents the solution state that best matches the available observations. The set of populations migrates to represent updated solution states as new observations are added over time. At the initial detection period, non-uniqueness is inherent in the source-identification due to inadequate information, and, consequently, several solutions may predict similarly well. To address nonuniqueness at the initial stages of the search and prevent premature convergence of the EA to an incorrect solution, the multiple populations in the proposed methodology are designed to maintain a set of alternative solutions representing different non-unique solutions. As more observations are added, the EA solutions not only migrate to better solution states, but also reduce the number of solutions as the degree of non-uniqueness diminishes. This new dynamic optimization algorithm adaptively converges to the best solution(s) to match the observations available at any time. The new method will be demonstrated for a contamination source identification problem in an illustrative water distribution network.}, booktitle={Water Distribution Systems Analysis Symposium 2006}, publisher={American Society of Civil Engineers}, author={Liu, Li and Zechman, Emily M. and Brill, Jr., E. Downey and Mahinthakumar, G. and Ranjithan, S. and Uber, James}, year={2008}, month={Mar} }
 @inproceedings{zechman_brill, jr._mahinthakumar_ranjithan_uber_2008, title={Addressing Non-uniqueness in a Water Distribution Contaminant Source Identification Problem}, ISBN={9780784409411}, url={http://dx.doi.org/10.1061/40941(247)126}, DOI={10.1061/40941(247)126}, abstractNote={The source of contamination in a water distribution system may be identified through a simulation-optimization approach. The optimization method searches for the contaminant source characteristics by iteratively estimating the contaminant plume concentrations until they match observations at sensors. The amount of information available for characterizing the source depends on the number and spatial locations of the sensors, as well as on the temporally varying stream of sensed data. The accuracy of the source characterization depends on the amount of observations available. A major factor affecting this accuracy is the degree of non-uniqueness present in the problem, which may cause misidentification of the source characteristics. As more sensors are added to the network, the non-uniqueness may be reduced and a unique solution may be identified. Thus, a key consideration when solving these problems is to assess whether the solution identified is unique, and if not, what other possible solutions are present. A systematic search for a set of alternatives that are maximally different in solution characteristics can be used to address and quantify non-uniqueness. For example, if the most different set of solutions that are identified by a search procedure are very similar, then that solution will be considered as the unique solution with a higher degree of certainty. Alternatively, identification of a set of maximally different solutions that vary widely in solution characteristics will indicate that nonuniqueness is present in the problem, and the range of solutions can be used as a general representation of the amount of non-uniqueness. This paper investigates the use of evolutionary algorithm (EA)-based alternatives generation procedures to quantify and address non-uniqueness present in a contaminant source identification problem for a water distribution network. As additional sensors may decrease the amount of non-uniqueness, several sensor configurations will be tested to investigate and quantify the improvement in uniqueness as more information is used in the source characterization.}, booktitle={Water Distribution Systems Analysis Symposium 2006}, publisher={American Society of Civil Engineers}, author={Zechman, Emily M. and Brill, Jr., E. Downey and Mahinthakumar, G. and Ranjithan, S. and Uber, James}, year={2008}, month={Mar} }
 @inproceedings{liu_brill, jr._mahinthakumar_ranjithan_2008, title={Contaminant Source Characterization Using Logistic Regression and Local Search Methods}, ISBN={9780784409763}, url={http://dx.doi.org/10.1061/40976(316)503}, DOI={10.1061/40976(316)503}, abstractNote={Given a set of contaminant concentration observations at sensors in a water distribution network, an inverse problem can be constructed to identify the contaminant source characteristics (including location, strength and release history) by coupling a water distribution simulation model with an optimization method. This approach, however, requires a large number of time-consuming simulation runs to evaluate potential solutions, and it may be difficult to converge on the best solution or set of possible solutions within a reasonable computational time. For this reason, it is desirable to appropriately reduce the decision space over which the optimization procedure must search to reduce the computational burden and to potentially produce faster convergence. We propose a method to reduce the decision space by efficiently identifying the probability of each point or demand node being a contaminant source location using mostly off-line computations. Then, the most likely source locations are used as a good starting point for local search methods to obtain the optimal injection profile(s) to match the observed concentration profile(s) over time. The proposed approach is demonstrated for a contamination source identification problem using an illustrative water distribution network.}, booktitle={World Environmental and Water Resources Congress 2008}, publisher={American Society of Civil Engineers}, author={Liu, Li and Brill, Jr., E. Downey and Mahinthakumar, G. and Ranjithan, S.}, year={2008}, month={May} }
 @inproceedings{kumar_brill_ranjithan_mahinthakumar_uber_2008, title={Source Identification for Contamination Events Involving Reactive Contaminants}, ISBN={9780784409763}, url={http://dx.doi.org/10.1061/40976(316)504}, DOI={10.1061/40976(316)504}, abstractNote={The problem of contaminant source identification in a water distribution system can be solved as an inverse problem using a simulation-optimization approach. The optimization method searches for contaminant source characteristics which lead to matching observations at the sensors. Accuracy of identification depends on the quantity and quality of data available at the sensors. The present state of the art in water quality monitoring sensors does not always allow for the detection of different kinds of contaminants in the system and they do not provide continuous contaminant concentration measurements. Some sensors provide an event detection trigger based on a specific concentration threshold yielding a binary detection/no-detection signal. Sensors also routinely monitor water quality parameters such as chlorine and pH. For example, a contaminant present in the system may react with chlorine leading to changes in chlorine-based water quality indicators. These anomalies (or deviations) in the observed water quality in the distribution system can be used as indicators of presence of contaminants in the system. A methodology for identifying the source characteristics using sensors outputting binary signals was presented by the authors recently. In the present study we investigate the interaction of reactive contaminants with chlorine in the system and its effect on water quality indicators. These anomalies indicating the presence or absence of contaminants will be used for determination of source characteristics using an evolutionary algorithm-based simulation-optimization approach.}, booktitle={World Environmental and Water Resources Congress 2008}, publisher={American Society of Civil Engineers}, author={Kumar, Jitendra and Brill, E. Downey and Ranjithan, S. Ranji and Mahinthakumar, G. and Uber, J.}, year={2008}, month={May} }
 @article{kumar_doby_baugh_brill_ranjithan_2007, title={Closure to "optimal design of redundant water distribution networks using a cluster of workstations" by Sujay V. Kumar, Troy A. Doby, John W. Baugh Jr., E. Downey Brill, and S. Ranji Ranjithan}, volume={133}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-36349011269&partnerID=MN8TOARS}, DOI={10.1061/(asce)0733-9496(2007)133:6(580)}, number={6}, journal={Journal of Water Resources Planning and Management}, author={Kumar, S. V. and Doby, T. A. and Baugh, John and Brill, E. D. and Ranjithan, S. R.}, year={2007}, pages={580–581} }
 @inproceedings{liu_brill, jr._mahinthakumar_uber_zechman_ranjithan_2007, title={Considering Demand Variability and Measurement Uncertainties in Adaptive Source Characterization in Water Distribution Networks}, ISBN={9780784409275}, url={http://dx.doi.org/10.1061/40927(243)502}, DOI={10.1061/40927(243)502}, abstractNote={Characterizing the sources of contamination in water distribution networks continues to be a challenging problem. Several methods have been reported to address this problem. The authors previously presented and continue to investigate an adaptive search procedure that attempts to solve this problem under dynamic conditions. Since demand variability and measurement errors contribute significantly to the quality of the solutions obtained as well as the time to solve the problem, we investigate these effects on the adaptive dynamic optimization procedure. First, the effects of these variabilities and uncertainties on the solutions obtained under deterministic conditions are evaluated. Second, we incorporate them such that the search for the source characterization is conducted under noisy conditions. This paper reports the results from these investigations based on an investigation conducted for an illustrative water distribution network.}, booktitle={World Environmental and Water Resources Congress 2007}, publisher={American Society of Civil Engineers}, author={Liu, Li and Brill, Jr., E. Downey and Mahinthakumar, G. and Uber, James and Zechman, Emily M. and Ranjithan, S.}, year={2007}, month={May} }
 @inbook{sreepathi_mahinthakumar_zechman_ranjithan_brill_ma_von laszewski_2007, place={Berlin Heidelberg}, series={Lecture Notes in Computer Science}, title={Cyberinfrastructure for Contamination Source Characterization in Water Distribution Systems}, ISBN={9783540725831 9783540725848}, ISSN={0302-9743 1611-3349}, url={http://dx.doi.org/10.1007/978-3-540-72584-8_139}, DOI={10.1007/978-3-540-72584-8_139}, abstractNote={This paper describes a preliminary cyberinfrastructure for contaminant characterization in water distribution systems and its deployment on the grid. The cyberinfrastructure consists of the application, middleware and hardware resources. The application core consists of various optimization modules and a simulation module. This paper focuses on the development of specific middleware components of the cyberinfrastructure that enables efficient seamless execution of the application core in a grid environment. The components developed in this research include: (i) a coarse-grained parallel wrapper for the simulation module that includes additional features for persistent execution, (ii) a seamless job submission interface, and (iii) a graphical real time application monitoring tool. The performance of the cyberinfrastructure is evaluated on a local cluster and the TeraGrid.}, booktitle={Computational Science – ICCS 2007}, publisher={Springer Berlin Heidelberg}, author={Sreepathi, Sarat and Mahinthakumar, Kumar and Zechman, Emily and Ranjithan, Ranji and Brill, Downey and Ma, Xiaosong and von Laszewski, Gregor}, editor={Shi, Y. and van Albada, G.D. and Dongarra, J. and Sloot, P.M.A.Editors}, year={2007}, pages={1058–1065}, collection={Lecture Notes in Computer Science} }
 @inproceedings{kumar_zechman_brill_mahinthakumar_ranjithan_uber_2007, title={Evaluation of Non-Uniqueness in Contaminant Source Characterization Based on Sensors with Event Detection Methods}, ISBN={9780784409275}, url={http://dx.doi.org/10.1061/40927(243)513}, DOI={10.1061/40927(243)513}, abstractNote={Due to the present state of sensor technology, during a water distribution contamination event, sensors may be able to detect only the presence of a contaminant and not necessarily the complete concentration profile. Some sensors trigger a detection based on a specified threshold concentration of observation, yielding a binary detection/no-detection signal. Event detection can also be based on observed concentrations of water quality parameters, such as pH and chlorine, which are routinely measured. These concentration observations are then processed through event detection algorithms to yield a detection/no-detection signal. These event detection techniques filter the measured concentrations at sensors to produce a discrete signal. When using this filtered information to characterize the contamination source, the certainty of identifying a unique solution is likely reduced, i.e., a set of widely different source characteristics may provide a match for the sensor observations. The authors previously presented an evolutionary algorithm-based procedure for source characterization and for assessing nonuniqueness by generating a set of maximally different alternatives. The procedure is extended here to characterize a contaminant source and any non-uniqueness arising by using sensor information processed through different event detection methods.}, booktitle={World Environmental and Water Resources Congress 2007}, publisher={American Society of Civil Engineers}, author={Kumar, Jitendra and Zechman, E. M. and Brill, E. D. and Mahinthakumar, G. and Ranjithan, S. and Uber, J.}, year={2007}, month={May} }
 @inbook{mahinthakumar_von laszewski_ranjithan_brill_uber_harrison_sreepathi_zechman_2006, place={Berlin Heidelberg}, series={Lecture Notes in Computer Science}, title={An Adaptive Cyberinfrastructure for Threat Management in Urban Water Distribution Systems}, volume={3993}, ISBN={9783540343837 9783540343844}, ISSN={0302-9743 1611-3349}, url={http://dx.doi.org/10.1007/11758532_54}, DOI={10.1007/11758532_54}, abstractNote={Threat management in drinking water distribution systems involves real-time characterization of any contaminant source and plume, design of control strategies, and design of incremental data sampling schedules. This requires dynamic integration of time-varying measurements along with analytical modules that include simulation models, adaptive sampling procedures, and optimization methods. These modules are compute-intensive, requiring multi-level parallel processing via computer clusters. Since real-time responses are critical, the computational needs must also be adaptively matched with available resources. This requires a software system to facilitate this integration via a high-performance computing architecture such that the measurement system, the analytical modules and the computing resources can mutually adapt and steer each other. This paper describes the development of such an adaptive cyberinfrastructure system facilitated by a dynamic workflow design.}, booktitle={Computational Science – ICCS 2006}, publisher={Springer}, author={Mahinthakumar, Kumar and von Laszewski, Gregor and Ranjithan, Ranji and Brill, Downey and Uber, Jim and Harrison, Ken and Sreepathi, Sarat and Zechman, Emily}, editor={Alexandrov, V.N. and Albada, G.D. and Sloot, P.M.A. and Dongarra, J.Editors}, year={2006}, pages={401–408}, collection={Lecture Notes in Computer Science} }
 @article{fu_brill_ranjithan_2006, title={Conjunctive use of models to design cost-effective ozone control strategies}, volume={56}, ISSN={["2162-2906"]}, DOI={10.1080/10473289.2006.10464492}, abstractNote={Abstract The management of tropospheric ozone (O3) is particularly difficult. The formulation of emission control strategies requires considerable information including: (1) emission inventories, (2) available control technologies, (3) meteorological data for critical design episodes, and (4) computer models that simulate atmospheric transport and chemistry. The simultaneous consideration of this information during control strategy design can be exceedingly difficult for a decision-maker. Traditional management approaches do not explicitly address cost minimization. This study presents a new approach for designing air quality management strategies; a simple air quality model is used conjunctively with a complex air quality model to obtain low-cost management strategies. A simple air quality model is used to identify potentially good solutions, and two heuristic methods are used to identify cost-effective control strategies using only a small number of simple air quality model simulations. Subsequently, the resulting strategies are verified and refined using a complex air quality model. The use of this approach may greatly reduce the number of complex air quality model runs that are required. An important component of this heuristic design framework is the use of the simple air quality model as a screening and exploratory tool. To achieve similar results with the simple and complex air quality models, it may be necessary to “tweak” or calibrate the simple model. A genetic algorithm-based optimization procedure is used to automate this tweaking process. These methods are demonstrated to be computationally practical using two realistic case studies, which are based on data from a metropolitan region in the United States.}, number={6}, journal={JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION}, author={Fu, Joshua S. and Brill, E. Downey, III and Ranjithan, S. Ranji}, year={2006}, month={Jun}, pages={800–809} }
 @article{kumar_doby_baugh_brill_ranjithan_2006, title={Optimal design of redundant water distribution networks using a cluster of workstations}, volume={132}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-33747304468&partnerID=MN8TOARS}, DOI={10.1061/(ASCE)0733-9496(2006)132:5(374)}, abstractNote={A genetic algorithm (GA)-based method for the least-cost design of looped pipe networks for various levels of redundancy is presented in this paper. Redundancy constraints are introduced in the optimization model by considering the number of pipes assumed to be out of service at any one time. Using this approach, trade-off relationships between cost and redundancy are developed. The GA-based approach is computationally intensive, and implementations on a custom fault-tolerant distributed computing framework, called Vitri, are used to satisfy the computational requirements. The design methodology is applied to two water distribution networks of different sizes, and a comparison of the performance of the distributed GAs for the design problems is also presented. We conclude that a GA-based approach to obtaining cost-effective, redundant solutions for the least-cost design of looped pipe networks can be effectively used on a heterogeneous network of nondedicated workstations.}, number={5}, journal={Journal of Water Resources Planning and Management}, author={Kumar, S. V. and Doby, T. A. and Baugh, John and Brill, E. D. and Ranjithan, S. R.}, year={2006}, pages={374–384} }
 @article{solano_dumas_harrison_ranjithan_barlaz_downey brill_2002, title={Life-Cycle-based Solid Waste Management. II: Illustrative Applications}, volume={128}, ISSN={0733-9372 1943-7870}, url={http://dx.doi.org/10.1061/(asce)0733-9372(2002)128:10(993)}, DOI={10.1061/(asce)0733-9372(2002)128:10(993)}, abstractNote={A companion paper described the development of the integrated solid waste management (ISWM) model that considers cost, energy, and environmental releases associated with management of municipal solid waste. This paper demonstrates the application of the ISWM model to a hypothetical, but realistic, case study. Several solid waste management (SWM) scenarios are studied, including the variation in energy and environmental emissions among alternate SWM strategies; the effect of mandated waste diversion (through recycling and other beneficial uses of waste such as combustion to recover energy) on environmental releases and cost; the tradeoff between cost and the level of waste diversion; and the tradeoff between cost and greenhouse gas emissions. In addition, the flexibility of the model is illustrated by the identification of alternate SWM strategies that meet approximately the same objectives using distinctly different combinations of unit processes. This flexibility may be of importance to local solid waste management planners who must implement new SWM programs. Use of the model illustrates the potential impact of solid waste management policies and regulations on global environmental emissions.}, number={10}, journal={Journal of Environmental Engineering}, publisher={American Society of Civil Engineers (ASCE)}, author={Solano, Eric and Dumas, Robert D. and Harrison, Kenneth W. and Ranjithan, S. Ranji and Barlaz, Morton A. and Downey Brill, E.}, year={2002}, month={Oct}, pages={993–1005} }
 @article{solano_ranjithan_barlaz_brill_2002, title={Life-cycle-based solid waste management. I: Model development}, volume={128}, DOI={10.1061/(asce)0733-9372(2002)128:10(981)}, abstractNote={This paper describes an integrated solid waste management (ISWM) model to assist in identifying alternative SWM strategies that meet cost, energy, and environmental emissions objectives. An SWM system consisting of over 40 unit processes for collection, transfer, separation, treatment (e.g., combustion, composting), and disposal of waste as well as remanufacturing facilities for processing recycled material is defined. Waste is categorized into 48 items and their generation rates are defined for three types of sectors: single-family dwelling, multifamily dwelling, and commercial. The mass flow of each item through all possible combinations of unit processes is represented in a linear programming model using a unique modeling approach. Cost, energy consumption, and environmental emissions associated with waste processing at each unit process are computed in a set of specially implemented unit process models. A life-cycle approach is used to compute energy consumption and emissions of CO, fossil- and biomas...}, number={10}, journal={Journal of Environmental Engineering (New York, N.Y.)}, author={Solano, E. and Ranjithan, S. R. and Barlaz, Morton and Brill, E. D.}, year={2002}, pages={981–992} }
 @article{harrison_dumas_solano_barlaz_brill_ranjithan_2001, title={Decision support tool for life-cycle-based solid waste management}, volume={15}, DOI={10.1061/(ASCE)0887-3801(2001)15:1(44)}, abstractNote={Existing solid waste management (SWM) planning software provides only limited assistance to decision makers struggling to find strategies that address their multifarious concerns. The combinatorial nature (many waste items and many management options) and multiple objectives of the SWM problem severely constrain the effectiveness of a manual search process using these tools. Recognizing this, researchers have proposed several optimization-based search procedures. These methods, however, enjoy limited use due to the substantial expertise required for their application. This paper presents a new computer-based decision support framework that addresses these limitations. The new framework integrates process models that quantify the life-cycle inventory of a range of pollutants and costs for an extensive municipal solid waste system, an optimization search procedure that identifies strategies that meet cost and environmental objectives and site-specific restrictions, and a user-friendly interface that facilitates utilization of these components by practitioners. After describing the software design, the use and value of the tool in typical waste management scenarios is demonstrated through a hypothetical, but realistic, case study in which several alternative SWM strategies are generated and examined.}, number={1}, journal={Journal of Computing in Civil Engineering}, author={Harrison, K. W. and Dumas, R. D. and Solano, E. and Barlaz, Morton and Brill, E. D. and Ranjithan, S. R.}, year={2001}, pages={44–58} }
 @article{loughlin_ranjithan_brill_baugh_2001, title={Genetic algorithm approaches for addressing unmodeled objectives in optimization problems}, volume={33}, ISSN={["0305-215X"]}, DOI={10.1080/03052150108940933}, abstractNote={Abstract Public sector decision-making typically involves complex problems that are often not completely understood. In these problems, there are invariably unmodeled issues that can greatly impact the acceptability of solutions. Modeling to Generate Alternatives (MGA) is an approach for addressing unmodeled issues in an optimization context. MGA techniques are used to generate a small number of good, yet very different, solutions to optimization problems. Because these solutions are different in decision space, they may differ considerably in performance when unmodeled objectives are considered. Many problems are sufficiently complex that traditional optimization solution procedures, and therefore traditional MGA techniques, are not readily applicable. Two techniques for performing MGA using genetic algorithms (GAs) are investigated and compared. One of these techniques, which uses specialized MGA operators, is shown to produce solutions that are both better in quality and more different. This technique is also demonstrated for a realistic air quality management problem.}, number={5}, journal={ENGINEERING OPTIMIZATION}, author={Loughlin, DH and Ranjithan, SR and Brill, ED and Baugh, JW}, year={2001}, pages={549–569} }
 @article{loughlin_ranjithan_baugh_brill_2000, title={Application of genetic algorithms for the design of ozone control strategies}, volume={50}, ISSN={["2162-2906"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-0034195231&partnerID=MN8TOARS}, DOI={10.1080/10473289.2000.10464133}, abstractNote={ABSTRACT Designing air quality management strategies is complicated by the difficulty in simultaneously considering large amounts of relevant data, sophisticated air quality models, competing design objectives, and unquantifiable issues. For many problems, mathematical optimization can be used to simplify the design process by identifying cost-effective solutions. Optimization applications for controlling nonlinearly reactive pollutants such as tropospheric ozone, however, have been lacking because of the difficulty in representing nonlinear chemistry in mathematical programming models. We discuss the use of genetic algorithms (GAs) as an alternative optimization approach for developing ozone control strategies. A GA formulation is described and demonstrated for an urban-scale ozone control problem in which controls are considered for thousands of pollutant sources simultaneously. A simple air quality model is integrated into the GA to represent ozone transport and chemistry. Variations of the GA formulation for multiobjective and chance-constrained optimization are also presented. The paper concludes with a discussion of the practicality of using more sophisticated, regulatory-scale air quality models with the GA. We anticipate that such an approach will be practical in the near term for supporting regulatory decision-making.}, number={6}, journal={JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION}, author={Loughlin, DH and Ranjithan, SR and Baugh, JW and Brill, ED}, year={2000}, month={Jun}, pages={1050–1063} }
 @inproceedings{ranjithan_barlaz_brill_dumas_harrison_kosmicki_solano_1998, title={Development of alternative solid waste management options with economic and environmental considerations: A mathematical modeling approach}, number={1998 Oct.}, booktitle={International Solid Waste Association 1998 World Congress, Charlotte, NC, Oct. 26-29, 1998}, author={Ranjithan, S. R and Barlaz, M. A. and Brill, E. D. and Dumas, R. D. and Harrison, K. W. and Kosmicki, B. A. and Solano, E.}, year={1998} }
 @inproceedings{loughlin_ranjithan_brill_baugh_fine_1998, title={Prototype decision support tool for developing tropospheric ozone control strategies}, booktitle={Water resources and the urban environment-98: Proceedings of the 1998 National Conference on Environmental Engineering. ASCE Joint 25th Annual Conference on Water Resources Planning and Management and 1998 National Conference on Environmental Engineering, Chicago, IL, June 7-10,1998}, publisher={Reston, VA: American Society of Civil Engineers}, author={Loughlin, D. and Ranjithan, S. and Brill, E. D. and Baugh, J. and Fine, S.}, year={1998} }
 @article{baugh_caldwell_brill_1997, title={A mathematical programming approach for generating alternatives in discrete structural optimization}, volume={28}, ISSN={["0305-215X"]}, DOI={10.1080/03052159708941125}, abstractNote={Structural design, like other complex decision problems, involves many tradeoffs among competing criteria. While mathematical programming models are increasingly realistic, there are often relevant issues that cannot be easily captured, if at all, in a formal system. This paper describes an approach to modelling that recognizes these limitations and allows a designer to explore unmodelled issues in a joint human-computer cognitive system. A prototype based on this approach is presented for topological truss optimization, and three modelling techniques are contrasted for their effectiveness in producing “different” alternatives. The results show that alternatives produced using these techniques are good with respect to modelled objectives, and yet are different, and often better, with respect to interesting objectives not present in the model.}, number={1-2}, journal={ENGINEERING OPTIMIZATION}, author={Baugh, JW and Caldwell, SC and Brill, ED}, year={1997}, pages={1–31} }
 @inbook{brill_1997, title={Effluent charges and transferable discharge permits}, booktitle={Design and operation of civil and environmental engineering systems}, publisher={New York: Wiley}, author={Brill, E. D.}, editor={C. ReVelle and McGarity, A. E.Editors}, year={1997}, pages={657–690} }