@misc{loughlin_barlaz_2006, title={Policies for strengthening markets for recyclables: A worldwide perspective}, volume={36}, ISSN={["1547-6537"]}, DOI={10.1080/10643380600566952}, abstractNote={Many national, regional, and local governments have introduced policies to encourage recycling. Their varied experiences allow examination of the effectiveness of alternative policy options. The conditions driving recycling, selection of pro-recycling policies, and recycling statistics are compared for 14 countries across Europe, Asia, North America, South America, and Oceana. The best policy for any particular country is a function of practicality, affordability, and political and social acceptability. National programs with the highest recycling rates typically target both supply and demand through incentives that encourage source separation and recycled content, with regulatory measures used to close loopholes and provide minimum performance requirements.}, number={4}, journal={CRITICAL REVIEWS IN ENVIRONMENTAL SCIENCE AND TECHNOLOGY}, author={Loughlin, DH and Barlaz, MA}, year={2006}, pages={287–326} }
 @article{doby_loughlin_reyes_ducoste_2002, title={Optimization of activated sludge designs using genetic algorithms}, volume={45}, ISSN={["0273-1223"]}, url={http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=ORCID&SrcApp=OrcidOrg&DestLinkType=FullRecord&DestApp=WOS_CPL&KeyUT=WOS:000175103800019&KeyUID=WOS:000175103800019}, DOI={10.2166/wst.2002.0106}, abstractNote={We describe a framework in which a genetic algorithm (GA) and a static activated sludge (AS) treatment plant design model (WRC AS model) are used to identify low cost activated sludge designs that meet specified effluent limits (e.g. for BOD, N, and P). Once the user has chosen a particular process (Bardenpho, Biodenipho, UCT or SBR), this approach allows the parameterizations for each AS unit process to be optimized systematically and simultaneously. The approach is demonstrated for a wastewater treatment plant design problem and the GA-based performance is compared to that of a classical nonlinear optimization approach. The use of GAs for multiobjective problems such as AS design is demonstrated and their application for reliability-based design and alternative generation is discussed.}, number={6}, journal={WATER SCIENCE AND TECHNOLOGY}, author={Doby, TA and Loughlin, DH and Reyes, FL and Ducoste, JJ}, year={2002}, pages={187–198} }
 @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{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} }