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Improved mixed-integer linear programming model and heuristics for bi-objective single-machine batch scheduling with energy cost consideration
Authors:Shibohua Zhang  Xueqi Wu  Chengbin Chu
Affiliation:1. School of Management, Northwestern Polytechnical University, Xi’an, People’s Republic of China;2. Laboratoire Génie Industriel, Centrale Supélec, Université Paris-Saclay, Chatenay-Malabry, France;3. Laboratoire Génie Industriel, Centrale Supélec, Université Paris-Saclay, Chatenay-Malabry, France
Abstract:This article addresses bi-objective single-machine batch scheduling under time-of-use electricity prices to minimize the total energy cost and the makespan. The lower and upper bounds on the number of formed batches are first derived and a continuous-time mixed-integer linear programming model is proposed, which improves an existing discrete-time model in the literature. Two improved heuristics are proposed based on the improved model. Computational experiments demonstrate that the improved model and heuristics can run hundreds of times faster than the existing ones for large-size instances.
Keywords:Single-machine batch scheduling  time-of-use (TOU) electricity prices  bi-objective optimization  mixed-integer linear programming (MILP)  heuristics
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