http://orcid.org/0000-0002-9960-0465
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Abstract
Make-To-Order (MTO) is a popular production strategy commonly used by manufacturers selling customized products. Dynamic pricing is a popular tactical tool commonly used by sellers to match supply with demand when there is a limited capacity and high demand uncertainty over time. In this article, we consider joint pricing and production scheduling decisions faced by a manufacturer that uses an MTO strategy to sell a number of customized products made from a common base product. At the beginning of each period in a planning horizon, the manufacturer sets the price of the base product, which in turn sets the prices for the customized products accordingly. Given the prices, orders for the products arrive. In each period, together with the pricing decision, the manufacturer needs to make a production scheduling decision for processing accepted orders on a single production line. The manufacturer’s objective is to maximize the total revenue of the processed orders minus a scheduling penalty over the planning horizon. Three specific problems with different order acceptance rules and objective functions are studied. In the first problem, the manufacturer has to accept all the incoming orders and treats the total weighted completion time of the orders as a part of the objective function. In the second problem, the manufacturer has to accept all incoming orders, but is allowed to complete some orders after their due dates with tardiness penalties. In the third problem, the manufacturer may reject some incoming orders, but must complete all the accepted orders by their due dates. We show that all these problems are NP-hard, propose optimal pseudo-polynomial-time dynamic programming algorithms and fully-polynomial-time approximation schemes for solving these problems, and conduct computational experiments to show the performance of the proposed algorithms. Furthermore, we derive several managerial insights through computational experiments.
Acknowledgments
We would like to thank the three anonymous referees for their constructive comments and suggestions that helped us to strengthen this article and improve its readability.
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Notes on contributors
Qing Yue
Qing Yue is an assistant professor at the Department of Business Management and Economics, Shanghai University of International Business and Economics. Her research interests include integrated pricing and scheduling, appointment scheduling, and data-driven operations research. She has published in the Journal of the Operational Research Society and others.
Zhi-Long Chen
Zhi-Long Chen is a professor of management science at the Robert H. Smith School of Business, University of Maryland, College Park, Maryland, USA. His research interests include supply chain scheduling, transportation and logistics operations, and dynamic pricing. This is his 60th published paper. In addition to IIE Transactions, his papers have also appeared in journals such as EJOR, INFORMS Journal on Computing, M&SOM, Naval Research Logistics, Operations Research, POM, and Transportation Science.
Guohua Wan
Guohua Wan is a professor of management science in the Antai College of Economics and Management, Shanghai Jiao Tong University, China. He received his Ph.D. from the Hong Kong University of Science and Technology. His research interests are operations planning and scheduling, supply chain optimization and IT for operations management. He has published in journals such as Operations Research, Management Science, Mathematics of Operations Research, and INFORMS Journal on Computing. He currently serves as a senior editor of Production and Operations Management.