Volume 50, Number 4-5, October-December 2016
Special issue - Advanced Optimization Approaches and Modern OR-Applications
|Page(s)||715 - 732|
|Published online||03 November 2016|
Bi-objective optimization of single-machine batch scheduling under time-of-use electricity prices
1 School of Management, Northwestern Polytechnical University,
Xi’an, P.R. China.
2 Laboratoire IBISC, University of Evry-Val d’Essonne, Evry, France.
3 School of Transportation Engineering, Hefei University of Technology, Hefei, P.R. China.
4 Laboratoire Genie Industriel, CentraleSupélec, Université Paris-Saclay, Grande Voie des Vignes, 92290 Chatenay-Malabry, France.
Accepted: 2 December 2015
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.
Mathematics Subject Classification: 90B35 / 90B50 / 90C11
Key words: Batch scheduling / TOU pricing policy / bi-objective optimization / makespan / electricity cost
© EDP Sciences, ROADEF, SMAI 2016
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