@article{fukuzawa_mcconnell_kay_thoney-barletta_warsing_2024, title={Implementing trades of the National Football League Draft on blockchain smart contracts}, volume={1}, ISSN={["2515-7841"]}, url={https://doi.org/10.1108/IJSMS-09-2023-0185}, DOI={10.1108/IJSMS-09-2023-0185}, abstractNote={PurposeDemonstrate proof-of-concept for conducting NFL Draft trades on a blockchain network using smart contracts.Design/methodology/approachUsing Ethereum smart contracts, the authors model several types of draft trades between teams. An example scenario is used to demonstrate contract interaction and draft results.FindingsThe authors show the feasibility of conducting draft-day trades using smart contracts. The entire negotiation process, including side deals, can be conducted digitally.Research limitations/implicationsFurther work is required to incorporate the full-scale depth required to integrate the draft trading process into a decentralized user platform and experience.Practical implicationsCutting time for the trade negotiation process buys decision time for team decision-makers. Gains are also made with accuracy and cost.Social implicationsFull-scale adoption may find resistance due to the level of fan involvement; the draft has evolved into an interactive experience for both fans and teams.Originality/valueThis research demonstrates the new application of smart contracts in the inter-section of sports management and blockchain technology.}, journal={INTERNATIONAL JOURNAL OF SPORTS MARKETING & SPONSORSHIP}, author={Fukuzawa, Mathew B. and McConnell, Brandon M. and Kay, Michael G. and Thoney-Barletta, Kristin A. and Warsing, Donald P.}, year={2024}, month={Jan} }
 @article{rossetti_warsing_flynn_bozarth_2023, title={Complex and lean or lean and complex? The role of supply chain complexity in lean production}, volume={4}, ISSN={["1936-9743"]}, DOI={10.1007/s12063-023-00355-2}, abstractNote={Research on Lean indicates that its association with performance improvement, although compelling, is not uniformly positive. Prior researchers have posited that plants implementing Lean may become too lean or may only implement selected aspects without fully embracing Lean’s synergistic prescriptions. We explore another potential reason for lower-than-expected performance sometimes associated with Lean: supply chain complexity. Using survey data from 209 manufacturing plants in seven countries across three industry groups, we test two alternative mechanisms by which supply chain complexity may influence performance improvements expected from Lean: moderation and mediation. We find that, while supply chain complexity has very little moderating impact on this relationship, it mediates the relationship between Lean and performance. While the majority of the significant mediating effects are negative, serving as a tax on Lean’s effect on performance, our analysis reveals some positive mediating effects, highlighting the difference between dysfunctional and strategic supply chain complexity. Our results indicate that managers should reduce internal and upstream complexity to improve Lean’s effect on performance. In particular, reducing the number of inputs a plant must manage has the widest and largest effect on realizing Lean’s positive influence on performance. Further, we highlight the importance of reducing dysfunctional supply chain complexity, while developing strategies to accommodate strategic supply chain complexity.}, journal={OPERATIONS MANAGEMENT RESEARCH}, author={Rossetti, Christian L. and Warsing, Donald P. and Flynn, Barbara B. and Bozarth, Cecil C.}, year={2023}, month={Apr} }
 @article{kapadia_uzsoy_starly_warsing_2021, title={A genetic algorithm for order acceptance and scheduling in additive manufacturing}, volume={10}, ISSN={["1366-588X"]}, DOI={10.1080/00207543.2021.1991023}, abstractNote={ABSTRACT We consider the problem of order acceptance and scheduling faced by an additive manufacturing facility consisting of multiple build chambers and postprocessing operations for support removal and surface finishing. We model each build chamber as a batch processing machine with processing times determined by the nesting and orientation of parts within the chamber. Due to the difficulty of developing an explicit functional relation between part batching, batch processing time, and postprocessing requirements we develop random-keys based genetic algorithms to select orders for complete or partial acceptance and produce a high-quality schedule satisfying all technological constraints, including part orientation and rotation within the build chamber. Extensive computational experiments show that the proposed approaches yield significant improvements in profit over the situation where all orders must be accepted, and produce solutions that compare favourably to statistically estimated bounds.}, journal={INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH}, author={Kapadia, Maaz Saleem and Uzsoy, Reha and Starly, Binil and Warsing, Donald P., Jr.}, year={2021}, month={Oct} }
 @article{luo_ahiska_fang_king_warsing_wu_2021, title={An analysis of optimal ordering policies for a two-supplier system with disruption risk}, volume={105}, url={https://doi.org/10.1016/j.omega.2021.102517}, DOI={10.1016/j.omega.2021.102517}, abstractNote={• Optimal policy can be proved for a two-supplier system with an unreliable supplier. • Stable (s,S) policy is robust outside of parameter conditions for optimality. • There is an easily computed condition for exclusive unreliable supplier ordering. • Optimal policies move from exclusive ordering to splitting as key parameters vary. We study a single-product, periodic-review inventory system with the presence of fixed ordering cost. There are two suppliers: One is perfectly reliable while the other offers a cost advantage but is subject to possible supply interruptions. We present a theoretical framework with mathematical proofs for the optimal ordering policy in the finite-horizon setting, which exhibits an ( s , S ) structure, but with multiple, sometimes overlapping, reorder points and order-up-to levels. Then, we analyze the limiting behavior of our ( s , S ) policy and show that both the optimal cost and ordering policy parameters converge over time. This steady-state ( s , S ) policy characterizes the optimal sourcing strategy for the infinite-horizon setting. Through computational studies, we investigate the effects of parameter changes on the optimal policy and demonstrate that our two-supplier ( s , S ) ordering policy is optimal under a wide range of system parameters beyond the conditions required in the optimality proof.}, journal={Omega - The International Journal of Management Science}, publisher={Elsevier BV}, author={Luo, Sha and Ahiska, S. Sebnem and Fang, Shu-Cherng and King, Russell E. and Warsing, Donald P., Jr. and Wu, Shuohao}, year={2021}, month={Dec}, pages={102517} }
 @article{moheb-alizadeh_handfield_warsing_2021, title={Efficient and sustainable closed-loop supply chain network design: A two-stage stochastic formulation with a hybrid solution methodology}, volume={308}, ISSN={["1879-1786"]}, DOI={10.1016/j.jclepro.2021.127323}, abstractNote={In recent years, consumers and legislators have pushed companies to design their supply chain networks to consider environmental and social impacts as an important performance outcome. Due to the role of resource utilization as a key component of logistics network design, another primary goal of design is ensuring available scarce resources are used as efficiently as possible across all facilities. To address efficiency issues in a sustainable closed-loop supply chain network, a stochastic integrated multi-objective mixed integer nonlinear programming model is developed in this paper, in which sustainability outcomes as well as efficiency of facility resource utilization are considered in the design of a sustainable supply chain network. In doing so, efficiency is assessed using a bi-objective output-oriented data envelopment analysis model. A hybrid three-step solution methodology is presented that creates a linear form of the original mixed integer nonlinear programming problem using piecewise McCormick envelopes approach. In the second step, an aggregated single objective programming model is derived by exploiting the multi-choice goal programming. Finally, a Lagrangian relaxation algorithm is developed to effectively solve the latter stochastic single objective mixed integer linear programming problem. The application of the proposed approach is investigated with data drawn from a case study in the electronics industry. This case study illustrates how firms may balance sustainability and efficiency in the supply chain network design problem. Further, it demonstrates the integration of efficiency results in improving economic aspects of sustainability as well as social responsibility outcomes, but also highlights the trade-offs that exist between efficiency and environmental impacts.}, journal={JOURNAL OF CLEANER PRODUCTION}, author={Moheb-Alizadeh, Hadi and Handfield, Robert and Warsing, Donald}, year={2021}, month={Jul} }
 @article{warsing_wangwatcharakul_king_2019, title={Computing base-stock levels for a two-stage supply chain with uncertain supply}, volume={89}, ISSN={0305-0483}, url={http://dx.doi.org/10.1016/J.OMEGA.2018.10.001}, DOI={10.1016/j.omega.2018.10.001}, abstractNote={We consider independent decision makers in a two-stage supply chain subject to uncertainty in upstream supply, and we use a recently published computational algorithm to generate independent, single-stage (ISS) base-stock inventory solutions for each stage in the system. These solutions are computed by employing straightforward, linear functions to estimate the parameters that must be set to seed the single-stage computational algorithm. Those linear functions are derived from the system-optimal solutions, which are found by solving a Markov chain model of the two-stage system. We demonstrate that the ISS solutions are often quite close to the system-optimal solution, and moreover, we develop a fast, descent-based search to quickly find the system-optimal solutions starting from the ISS solutions. We use our solution algorithm to generate optimal solutions to 1100 randomly-generated problem instances, allowing us to explore the behavior of the two-stage inventory system under various cost, demand uncertainty, and supply uncertainty conditions. We find that the downstream stocking levels are strongly influenced by the properties of the downstream demand, while the upstream stocking level is very strongly influenced by the holding costs and supply uncertainty, and only marginally by the retailer penalty cost. Moreover, the system responds to changes in the cost and uncertainty environment mostly by shifting the burden of holding cost either upstream or downstream, leaving the downstream penalty cost relative stable across the large set of problem instances we study.}, journal={Omega}, publisher={Elsevier BV}, author={Warsing, Donald P., Jr. and Wangwatcharakul, Worawut and King, Russell E.}, year={2019}, month={Dec}, pages={92–109} }
 @article{kapadia_starly_thomas_uzsoy_warsing_2019, title={Impact of Scheduling Policies on the Performance of an Additive Manufacturing Production System}, volume={39}, ISSN={2351-9789}, url={http://dx.doi.org/10.1016/j.promfg.2020.01.388}, DOI={10.1016/j.promfg.2020.01.388}, abstractNote={We study the impact of scheduling policies on the cycle time and throughput of an Additive Manufacturing (AM) facility. Orders for irregularly shaped parts with specified due dates and surface quality requirements arrive randomly at the facility. The parts are fabricated in one of several AM build chambers, followed by post-processing operations based on surface finishing requirements. We combine a part placement heuristic with different scheduling policies (FIFO, Earliest Due Date) to allocate parts to AM build chambers and lay out the parts within the chambers to approximately optimize delivery performance. Simulation experiments using an Iterative Optimization-based Simulation (IOS) model integrating a simulation engine (implemented in SIMIO) with a computational engine (implemented in MATLAB) show that the scheduling policies have a significant impact on cycle time and order lateness. Selection and peer review under the responsibility of ICPR25 International Scientific & Advisory and Organizing Committee members.}, journal={Procedia Manufacturing}, publisher={Elsevier BV}, author={Kapadia, Maaz Saleem and Starly, Binil and Thomas, Alec and Uzsoy, Reha and Warsing, Donald}, year={2019}, pages={447–456} }
 @article{nagulpelli_king_warsing_2019, title={Integrated traditional and additive manufacturing production profitability model}, volume={34}, ISSN={["2351-9789"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85072391087&partnerID=MN8TOARS}, DOI={10.1016/j.promfg.2019.06.121}, abstractNote={Production decision-makers now have a choice of production technologies. Decision-makers are familiar with “Traditional Manufacturing” (TM) technologies. In favorable circumstances, emerging “Additive Manufacturing” (AM) technology now offers more flexibility to modify the manufacturing environment and improve production logistics efficiency to enhance profits over a production schedule. This paper presents research, process methodologies, and a practical approach to the profit-based economic decision-modelling for production planning in a manufacturing environment resourced with both TM and AM technologies. The research identifies a framework for production leaders and managers to implement efficiency measures while adapting or refining AM production in an existing TM production environment. The paper also outlines opportunities for future research toward the objective of optimizing production technology assignments within a mixed-resource manufacturing environment.}, journal={47TH SME NORTH AMERICAN MANUFACTURING RESEARCH CONFERENCE (NAMRC 47)}, author={Nagulpelli, Kimberly S. and King, Russell E. and Warsing, Donald}, year={2019}, pages={619–630} }
 @article{karagul_warsing_hodgson_kapadia_uzsoy_2018, title={A comparison of mixed integer programming formulations of the capacitated lot-sizing problem}, volume={56}, ISSN={["1366-588X"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85035114913&partnerID=MN8TOARS}, DOI={10.1080/00207543.2017.1401232}, abstractNote={We propose a novel mixed integer programming formulation for the capacitated lot-sizing problem with set-up times and set-up carryover. We compare our formulation to two earlier formulations, the Classical and Modified formulations, and a more recent formulation due to Suerie and Stadtler. Extensive computational experiments show that our formulation consistently outperforms the Classical and Modified formulations in terms of CPU time and solution quality. It is competitive with the Suerie–Stadtler (S&S) formulation, but outperforms all other formulations on the most challenging instances, those with low-capacity slack and a dense jobs matrix. We show that some of the differences in the performance of these various formulations arise from their different use of binary variables to represent production or set-up states. We also show that the LP relaxation of our Novel formulation provides a tighter lower bound than that of the Modified formulation. Our experiments demonstrate that, while the S&S formulation provides a much tighter LP bound, the Novel formulation is better able to exploit the intelligence of the CPLEX solution engine.}, number={23}, journal={INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH}, author={Karagul, Hakan F. and Warsing, Donald P. and Hodgson, Thom J. and Kapadia, Maaz S. and Uzsoy, Reha}, year={2018}, pages={7064–7084} }
 @book{ravi ravindran_warsing_2016, title={Supply chain engineering: Models and applications}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85020077399&partnerID=MN8TOARS}, journal={Supply Chain Engineering: Models and Applications}, author={Ravi Ravindran, A. and Warsing, D.P.}, year={2016}, pages={1–548} }
 @inproceedings{wu_kay_king_vila-parrish_warsing_2014, title={Multi-objective optimization of 3D packing problem in additive manufacturing}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84910090427&partnerID=MN8TOARS}, booktitle={IIE Annual Conference and Expo 2014}, author={Wu, S. and Kay, M. and King, R. and Vila-Parrish, A. and Warsing, D.}, year={2014}, pages={1485–1494} }
 @article{ahiska_appaji_king_warsing_2013, title={A Markov decision process-based policy characterization approach for a stochastic inventory control problem with unreliable sourcing}, volume={144}, ISSN={["1873-7579"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84878827602&partnerID=MN8TOARS}, DOI={10.1016/j.ijpe.2013.03.021}, abstractNote={We consider a single-product periodic-review inventory system for a retailer who has adopted a dual sourcing strategy to cope with potential supply process interruptions. Orders are placed to a perfectly reliable supplier and/or to a less reliable supplier that offers a better price. The success of an order placed to the unreliable supplier depends on his supply status that has a Markovian nature. The inventory control problem for this unreliable supply chain is modeled as a discrete-time Markov decision process (MDP) in order to find the optimal ordering decisions. Through numerical experimentation, the structure of the optimal ordering policy under several cost scenarios and different supplier reliability levels is determined. Four basic policy structures are found and are referred as case 1: order only from the unreliable supplier; case 2: order simultaneously from both suppliers or only from the unreliable supplier depending on the inventory level; case 3: order from one or the other but not both suppliers simultaneously; and case 4: order only from the reliable supplier. For all cases, (s, S)-like policies characterize perfectly the optimal ordering decisions due to the existence of the fixed ordering cost. Further experimentation is done to study the effects of changes in several system parameters (cost parameters such as fixed ordering cost, unit purchasing cost, backorder cost as well as the supplier reliability level) on the ordering policy and cost of the system.}, number={2}, journal={INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS}, author={Ahiska, S. Sebnem and Appaji, Samyuktha R. and King, Russell E. and Warsing, Donald P., Jr.}, year={2013}, month={Aug}, pages={485–496} }
 @inproceedings{buch_king_vila-parrish_warsing_2013, title={A newsvendor problem with replenishment}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84900327424&partnerID=MN8TOARS}, booktitle={IIE Annual Conference and Expo 2013}, author={Buch, N. and King, R.E. and Vila-Parrish, A. and Warsing, D.P.}, year={2013}, pages={3934–3943} }
 @article{comparing traditional and fuzzy-set solutions to (q, r) inventory systems with discrete lead-time distributions_2013, volume={24}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84872357892&partnerID=MN8TOARS}, DOI={10.3233/IFS-2012-0533}, abstractNote={Using a previously published approach to computing Q, r policies for an inventory system with uncertain parameters described by fuzzy sets, we compare thee methods for specifying lead-time demand for four different empirically-specified, non-normal distributions of replenishment lead time. This general distribution of lead time results in a situation in which the distribution of demand over the lead time, or lead-time demand LTD, is not easily specified. We compare Q, r policies generated by using a traditional normal approximation to LTD, a fuzzy-set approximation, and the optimal policy computed via a simulation-optimization approach that utilizes the explicit LTD distribution. We show that, on average, the results from the fuzzy-set model are significantly more accurate than the traditional normal approximation, especially when the LTD distribution is highly skewed.}, number={1}, journal={Journal of Intelligent and Fuzzy Systems}, year={2013}, pages={93–104} }
 @article{wu_warsing_2013, title={Comparing traditional and fuzzy-set solutions to (Q, r) inventory systems with discrete lead-time distributions}, volume={24}, number={1}, journal={Journal of Intelligent & Fuzzy Systems}, author={Wu, X. M. and Warsing, D. P.}, year={2013}, pages={93–104} }
 @article{warsing_wangwatcharakul_king_2013, title={Computing optimal base-stock levels for an inventory system with imperfect supply}, volume={40}, ISSN={0305-0548}, url={http://dx.doi.org/10.1016/j.cor.2013.04.001}, DOI={10.1016/j.cor.2013.04.001}, abstractNote={We study a single-item, single-site, periodic-review inventory system with negligible fixed ordering costs. The supplier to this system is not entirely reliable, such that each order is a Bernoulli trial, meaning that, with a given probability, the supplier delivers the current order and any accumulated backorders at the end of the current period, resulting in a Geometric distribution for the actual resupply lead time. We develop a recursive expression for the steady-state probability vector of a discrete-time Markov process (DTMP) model of this imperfect-supply inventory system. We use this recursive expression to prove the convexity of the inventory system objective function, and also to prove the optimality of our computational procedure for finding the optimal base-stock level. We present a service-constrained version of the problem and show how the computation of the optimal base-stock level using our DTMP method, incorporating the explicit distribution of demand over the lead time plus review (LTR) period, compares to approaches in the literature that approximate this distribution. We also show that the version of the problem employing an explicit penalty cost can be solved in closed-form for the optimal base-stock level for two specific period demand distributions, and we explore the behavior of the optimal base-stock level and the corresponding optimal service level under various values of the problem parameters.}, number={11}, journal={Computers & Operations Research}, publisher={Elsevier BV}, author={Warsing, Donald P., Jr. and Wangwatcharakul, Worawut and King, Russell E.}, year={2013}, month={Nov}, pages={2786–2800} }
 @inproceedings{buch_king_vila-parrish_warsing_2012, title={An inventory model with restricted replenishment opportunities and re-estimated demand}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84900300196&partnerID=MN8TOARS}, booktitle={62nd IIE Annual Conference and Expo 2012}, author={Buch, N. and King, R.E. and Vila-Parrish, A.R. and Warsing, D.P.}, year={2012}, pages={531–539} }
 @inproceedings{lavin_king_vila-parrish_warsing_ahiska_2012, title={Infinite horizon periodic review perturbed demand model with lead time}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84900339479&partnerID=MN8TOARS}, booktitle={62nd IIE Annual Conference and Expo 2012}, author={Lavin, J.A. and King, R.E. and Vila-Parrish, A.R. and Warsing, D.P. and Ahiska, S.S.}, year={2012}, pages={540–547} }
 @inproceedings{wang_warsing_king_vila-parrish_sebnem ahiska_2012, title={Unreliable supplier selection with fixed costs and order constraints}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84900342003&partnerID=MN8TOARS}, booktitle={62nd IIE Annual Conference and Expo 2012}, author={Wang, Y. and Warsing, D.P. and King, R.E. and Vila-Parrish, A. and Sebnem Ahiska, S.}, year={2012}, pages={280–289} }
 @inproceedings{wang_king_ahiska_warsing_2011, title={Optimal ordering policy with multiple unreliable suppliers}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84900342045&partnerID=MN8TOARS}, booktitle={61st Annual IIE Conference and Expo Proceedings}, author={Wang, Y. and King, R.E. and Ahiska, S.S. and Warsing, D.P.}, year={2011} }
 @inproceedings{ahiska_appaji_king_wang_warsing_2010, title={Optimal ordering policy characterization in an unreliable supply chain}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84901009083&partnerID=MN8TOARS}, booktitle={IIE Annual Conference and Expo 2010 Proceedings}, author={Ahiska, S.S. and Appaji, S.R. and King, R.E. and Wang, Y. and Warsing, D.P.}, year={2010} }
 @article{handfield_warsing_wu_2009, title={(Q, r) Inventory policies in a fuzzy uncertain supply chain environment}, volume={197}, ISSN={["1872-6860"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-60649115627&partnerID=MN8TOARS}, DOI={10.1016/j.ejor.2008.07.016}, abstractNote={Managers have begun to recognize that effectively managing risks in their business operations plays an important role in successfully managing their inventories. Accordingly, we develop a (Q,r) model based on fuzzy-set representations of various sources of uncertainty in the supply chain. Sources of risk and uncertainty in our model include demand, lead time, supplier yield, and penalty cost. The naturally imprecise nature of these risk factors in managing inventories is represented using triangular fuzzy numbers. In addition, we introduce a human risk attitude factor to quantify the decision maker’s attitude toward the risk of stocking out during the replenishment period. The total cost of the inventory system is computed using defuzzification methods built from techniques identified in the literature on fuzzy sets. Finally, we provide numerical examples to compare our fuzzy-set computations with those generated by more traditional models that assume full knowledge of the distributions of the stochastic parameters in the system.}, number={2}, journal={EUROPEAN JOURNAL OF OPERATIONAL RESEARCH}, author={Handfield, Robert and Warsing, Don and Wu, Xinmin}, year={2009}, month={Sep}, pages={609–619} }
 @article{kay_warsing_2009, title={Estimating LTL rates using publicly available empirical data}, volume={12}, ISSN={["1469-848X"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-67650902017&partnerID=MN8TOARS}, DOI={10.1080/13675560802392415}, abstractNote={We develop a shipper-oriented model to estimate less-than-truckload (LTL) truck rates for transporting goods between origin–destination (O–D) pairs located anywhere in the continental United States. The rate estimate is developed from internet-accessible tariff tables and allows straightforward computation of optimal shipment sizes (minimising total logistics costs) and comparison with the total cost of other modes. The model uses publicly available nominal rates along with a characterisation of the distribution of LTL shipments, based on other publicly available data, to determine a rate that also accounts for the estimated industry average discount from the nominal rate. We use nonlinear regression to build the estimate, with tariff-based rates serving as the dependent variable and load density, shipment weight, and O–D pair distance as the explanatory variables. The model is normalised to reflect average industry rates and current economic conditions using the Producer Price Index for LTL service. Although our results are specific to US markets for truck freight, the method of analysis serves as a model for similar international studies.}, number={3}, journal={INTERNATIONAL JOURNAL OF LOGISTICS-RESEARCH AND APPLICATIONS}, author={Kay, Michael G. and Warsing, Donald P.}, year={2009}, pages={165–193} }
 @article{thomas_warsing_zhang_2009, title={Forecast updating and supplier coordination for complementary component purchases}, volume={18}, DOI={10.3401/poms.1080.01012}, number={2}, journal={Production and Operations Management}, author={Thomas, D. J. and Warsing, Donald and Zhang, X. Y.}, year={2009}, pages={167–184} }
 @article{thomas_warsing_zhang_2009, title={Forecast updating and supplier coordination for complementary component purchases}, volume={18}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-67549088044&partnerID=MN8TOARS}, DOI={10.1111/j.1937-5956.2009.01012.x}, abstractNote={We study a supply chain where an original equipment manufacturer (OEM) buys subassemblies, comprised of two complementary sets of components, from a contract manufacturer (CM). The OEM provides a demand forecast at the time when the CM must order the long lead‐time set of components, but must decide whether or not to provide updated forecasts as a matter of practice. Forecast updates affect the CM's short lead‐time purchase decision, and the anticipation of updates may also affect the long lead‐time purchase decision. While the OEM and CM both incur lost sales costs, the OEM can decide whether or not to share the overage costs otherwise fully borne by the CM. We investigate when the OEM is better served by committing to provide updated forecasts and/or committing to share overage costs. For a distribution‐free, two‐stage forecast‐update model, we show that (1) the practice of providing forecast updates may be harmful to the OEM and (2) at the OEM's optimal levels of overage risk sharing, the CM undersupplies relative to the supply chain optimal quantity. For a specific forecast‐update model, we computationally investigate conditions under which forecast updating and risk sharing are in the best interest of the OEM.}, number={2}, journal={Production and Operations Management}, author={Thomas, D.J. and Warsing, D.P. and Zhang, X.}, year={2009}, pages={167–184} }
 @article{gilland_warsing_2009, title={The Impact of Revenue-Maximizing Priority Pricing on Customer Delay Costs}, volume={40}, ISSN={["0011-7315"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-61849115209&partnerID=MN8TOARS}, DOI={10.1111/j.1540-5915.2008.00217.x}, abstractNote={Speed is an increasingly important determinant of which suppliers will be given customers' business and is defined as the time between when an order is placed by the customer and when the product is delivered, or as the amount of time customers must wait before they receive their desired service. In either case, the speed a customer experiences can be enhanced by giving priority to that particular customer. Such a prioritization scheme will necessarily reduce the speed experienced by lower-priority customers, but this can lead to a better outcome when different customers place different values on speed. We model a single resource (e.g., a manufacturer) that processes jobs from customers who have heterogeneous waiting costs. We analyze the price that maximizes priority revenue for the resource owner (i.e., supplier, manufacturer) under different assumptions regarding customer behavior. We discover that a revenue-maximizing supplier facing self-interested customers (i.e., those that independently minimize their own expected costs) charges a price that also minimizes the expected total delay costs across all customers and that this outcome does not result when customers coordinate to submit priority orders at a level that seeks to minimize their aggregate costs of priority fees and delays. Thus, the customers are better off collectively (as is the supplier) when the supplier and customers act independently in their own best interests. Finally, as the number of priority classes increases, both the priority revenues and the overall customer delay costs improve, but at a decreasing rate.}, number={1}, journal={DECISION SCIENCES}, author={Gilland, Wendell G. and Warsing, Donald P.}, year={2009}, month={Feb}, pages={89–120} }
 @article{bozarth_warsing_flynn_flynn_2009, title={The impact of supply chain complexity on manufacturing plant performance}, volume={27}, ISSN={["1873-1317"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-57649108561&partnerID=MN8TOARS}, DOI={10.1016/j.jom.2008.07.003}, abstractNote={Abstract This paper puts forth a model of supply chain complexity and empirically tests it using plant‐level data from 209 plants across seven countries. The results show that upstream complexity, internal manufacturing complexity, and downstream complexity all have a negative impact on manufacturing plant performance. Furthermore, supply chain characteristics that drive dynamic complexity are shown to have a greater impact on performance than those that drive only detail complexity. In addition to providing a definition and empirical test of supply chain complexity, the study serves to link the systems complexity literature to the prescriptions found in the flexibility and lean production literatures. Finally, this research establishes a base from which to extend previous work linking operations strategy to organization design [Flynn, B.B., Flynn, E.J., 1999. Information‐processing alternatives for coping with manufacturing environment complexity. Decision Sciences 30 (4), 1021–1052].}, number={1}, journal={JOURNAL OF OPERATIONS MANAGEMENT}, author={Bozarth, Cecil C. and Warsing, Donald P. and Flynn, Barbara B. and Flynn, E. James}, year={2009}, month={Jan}, pages={78–93} }
 @inbook{warsing_2008, title={Supply chain management}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85056984750&partnerID=MN8TOARS}, booktitle={Operations Research Applications}, author={Warsing, D.P.}, year={2008}, pages={8–1-8–64} }
 @inproceedings{bucci_kay_warsing_2007, title={A comparison of meta-heuristics for large scale facility location problems with economies of scale}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-44949149427&partnerID=MN8TOARS}, booktitle={IIE Annual Conference and Expo 2007 - Industrial Engineering's Critical Role in a Flat World - Conference Proceedings}, author={Bucci, M.J. and Kay, M.G. and Warsing, D.P.}, year={2007}, pages={1410–1415} }
 @article{thomas_warsing_2007, title={A periodic inventory model for stocking modular components}, volume={16}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-34547327241&partnerID=MN8TOARS}, DOI={10.1111/j.1937-5956.2007.tb00263.x}, abstractNote={We study the benefit obtained by exploiting modular product design in fulfilling exogenous demand for both a complete assembly and its components in a service parts inventory system. Our goal is to reduce overall service system costs by allowing assembly and/or disassembly (A/D) to occur at some unit cost per A/D action. In an extensive set of computational experiments, we compare a naïve stocking and operating policy that treats all items independently and ignores the modular product structure and related A/D capability to the optimal base stock policy, and to a policy that allows A/D from the naïve stocking levels. While extensive computational analysis shows that the optimal base stock policy improves the system cost between 3 to 26% over the naïve approach, simply allowing A/D from the naïve stocking levels captures a significant portion (an average of 67%) of the naïve–optimal gap. Our computational results demonstrate that the optimization shifts the component‐assembly mix from the naïve levels and that limiting A/D capacity affects this mix. Limiting A/D capacity can actually increase the expected number of A/D actions (versus the uncapacitated case), since the optimization shifts stocking levels to reduce the probability that “too many” actions will be required.}, number={3}, journal={Production and Operations Management}, author={Thomas, D.J. and Warsing, Donald}, year={2007}, pages={343–359} }
 @inproceedings{warsing_helmer_blackhurst_2006, title={Strategic safety stock placement in production networks with supply risk}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-36448975542&partnerID=MN8TOARS}, booktitle={2006 IIE Annual Conference and Exhibition}, author={Warsing, D.P. and Helmer, E.A. and Blackhurst, J.V.}, year={2006} }
 @article{warsing_souza_greis_2001, title={Determining the value of dedicated multimodal cargo facilities in a multi-region distribution network}, volume={133}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-0035899609&partnerID=MN8TOARS}, DOI={10.1016/S0377-2217(00)00185-5}, abstractNote={This paper presents an analytic model of a multi-region distribution problem that addresses the operational benefits of serving a global market using a network of dedicated multimodal cargo facilities (DMCFs). The model allows an explicit evaluation of the comparative value of using a dedicated air cargo-based multimodal distribution facility in an established network of supply and demand points as opposed to more traditional methods for inter-regional shipments. We develop a large-scale, non-linear programming model to evaluate the corresponding logistics costs, incorporating the congestion effects of aircraft loading/unloading on dock-to-dock lead times in the network. We then demonstrate how this difficult problem can be decomposed into its linear (LP) and non-linear (multi-class queueing) sub-problems. An iterative solution scheme is devised to compute the comparative costs of traditional and DMCF-based cargo operations.}, number={1}, journal={European Journal of Operational Research}, author={Warsing, D.P. and Souza, G.C. and Greis, N.P.}, year={2001}, pages={81–93} }