Stochastic programming approaches for an energy-aware lot-sizing and sequencing problem with incentive

Abstract

Motivated by real challenges on energy management faced by industrial firms, we propose a novel way to reduce production costs by including the pricing of electricity in a multi-product lot-sizing problem. In incentive-based programs, when electric utilities face power consumption peaks, they request electricity-consuming firms to curtail their electric load, rewarding the industrial firms with incentives if they comply with the curtailment requests. Otherwise, industrial firms must pay financial penalties for an excessive electricity consumption. A two-stage stochastic formulation is presented to cover the case where a manufacturer wants to satisfy any curtailment request. A chance-constrained formulation is also proposed, and its relevance in practice is discussed. Finally, computational studies are conducted to compare mathematical models and highlight critical parameters and show potential savings when subscribing incentive-based programs. We show that the setup cost ratio, the capacity utilisation rate, the number of products and the timing of curtailment requests are critical parameters for manufacturers.

Keywords:

• Lot sizing
• optimisation
• stochastic programming
• incentive-based programs
• energy management

Acknowledgments

The authors would like to thank the three anonymous referees whose remarks and suggestions improved the quality of the article.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by Clemson University.

Notes on contributors

Antoine Perraudat

Antoine Perraudat is a postdoctoral fellow at the research department ‘Manufacturing Sciences and Logistics’ of Mines Saint-Etienne in its site of Gardanne, France. He works in collaboration with the semiconductor manufacturer STMicroelectronics to better manage, control and predict the fabrication times of products. He received his (CIFRE) Ph.D. in Industrial Engineering from Mines Saint-Etienne in 2021 after studying Industrial Engineering, Operations Research and Computer Science at Mines Saint-Etienne where he graduated in 2017.

Stéphane Dauzère-Pérès

Stéphane Dauzère-Pérès is Professor at Mines Saint-Etienne in its site of Gardanne, France, and Adjunct Professor at BI Norwegian Business School, Norway. He received the Ph.D. degree from Paul Sabatier University in Toulouse, France, in 1992 and the H.D.R. from Pierre and Marie Curie University, Paris, France, in 1998. He was a Postdoctoral Fellow at the Massachusetts Institute of Technology, U.S.A., in 1992 and 1993, and Research Scientist at Erasmus University Rotterdam, The Netherlands, in 1994. He has been Associate Professor and Professor from 1994 to 2004 at the Ecole des Mines de Nantes, France, where he headed the team ‘Production and Logistic Systems’ between 1999 and 2004. He was invited Professor at the Norwegian School of Economics and Business Administration (NHH), Norway, in 1999. Since March 2004, he is Professor at Mines Saint-Etienne, where he headed the research department ‘Manufacturing Sciences and Logistics’ from 2004 to 2013. His research interests broadly include modelling and optimisation of operations at various decision levels (from real-time to strategic) in manufacturing and logistics, with a special emphasis on production planning (lot sizing) and scheduling, on semiconductor manufacturing and on railway operations. He has published 88 papers in international journals and has contributed to more than 200 communications in national and international conferences. Stèphane Dauzère-Péès has coordinated numerous academic and industrial research projects, including 4 European projects and 26 industrial (CIFRE) PhD theses, and also 7 conferences. In particular, he co-organised in 2010 the first edition of the International Workshop on Lot Sizing which was held in Gardanne, France. In 2014, he created with Bernardo Almada-Lobo (University of Porto, Portugal) the EURO Working Group on Lot-Sizing (LOT), that he coordinated until 2018. He was runner-up in 2006 of the Franz Edelman Award Competition, and won the Best Applied Paper of the Winter Simulation Conference in 2013 and the EURO Award for the Best EJOR Paper in 2021.

Scott Jennings Mason

Dr. Scott J. Mason is a Principal Research Scientist in the Middle Mile Products and Tech group at Amazon. Middle mile (line haul) is moving large trucks and cargo airplanes full of inventory/packages from point-to-point within Amazon's network of fulfillment centres, sort centres, and delivery stations. Prior to joining Amazon, Dr. Mason spent 20 years in academia at the University of Arkansas (2000–2010) and most recently at Clemson University (2010–2020) where he served as the inaugural Fluor Endowed Chair in Supply Chain Optimisation and Logistics and a Professor of Industrial Engineering. Dr. Mason uses operations research techniques to model and analyse large-scale supply chain and facility logistics challenges for Amazon. He received his Ph.D. in Industrial Engineering from Arizona State University after earning B.S. and M.S. degrees from The University of Texas at Austin. He is a Fellow of the Institute of Industrial and Systems Engineers and a member of INFORMS.