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Bi-objective optimization of single-machine batch scheduling under time-of-use electricity prices

Abstract : Time-of-use (TOU) electricity pricing has been a common practice to enhance the peak load regulation capability of power grid. Meanwhile, it provides a good opportunity for industries to reduce energy costs, especially for energy-intensive ones, where batch scheduling is often involved. Majority of batch scheduling problems have been proved to be NP-hard, even for most single-machine environments. Optimizing batch scheduling under TOU policy in these industries will be of great significance. Single-machine batch scheduling is an important basis for more complicated shop scheduling problems. This paper investigates a bi-objective single-machine batch scheduling problem under TOU policy: the first objective is to minimize the makespan and the second is to minimize the total electricity costs. The considered problem is first formulated as a bi-objective mix-integer linear programming (MILP) model and is demonstrated to be NP-hard. Subsequently, the MILP is simplified by analyzing properties and search space for a Pareto optimal solution is greatly reduced. Then, an exact ε-constraint method is adapted to obtain its Pareto front, which is accelerated due to these properties. Finally, a preferable solution is recommended for decision makers via a fuzzy-logic-based approach. Computational results on randomly generated instances show the effectiveness of the proposed approach.
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Contributor : Chengbin Chu <>
Submitted on : Thursday, February 11, 2016 - 5:33:34 PM
Last modification on : Friday, October 16, 2020 - 2:16:03 PM

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Junheng Cheng, Feng Chu, Chengbin Chu, Weili Xia. Bi-objective optimization of single-machine batch scheduling under time-of-use electricity prices. RAIRO - Operations Research, EDP Sciences, 2016, 50 (4-5), pp.715-732. ⟨10.1051/ro/2015063⟩. ⟨hal-01273066⟩



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