Bi-objective optimization of a single machine batch scheduling problem with energy cost consideration. (20th November 2016)

• Record Type: Journal Article
• Authors: Wang, Shijin; Liu, Ming; Chu, Feng; Chu, Chengbin
• Is Part Of: Journal of cleaner production. Volume 137(2016)
• Page Start: 1205
• Page End: 1215
• Publication Date: 2016-11-20
• Subjects: Batch scheduling -- Bi-objective optimization -- Energy consumption cost -- Makespan -- Single machine; Factory and trade waste -- Management -- Periodicals; Manufactures -- Environmental aspects -- Periodicals; Déchets industriels -- Gestion -- Périodiques; Usines -- Aspect de l'environnement -- Périodiques; 628.5
• DOI: 10.1016/j.jclepro.2016.07.206
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: With the increasing energy price, the rapid growth of electricity demand and severe challenges for sustainable development, energy-efficient scheduling is becoming more and more important for power-intensive manufacturing industry, especially for batch production companies. This paper investigates a bi-objective single machine batch scheduling problem with non-identical job sizes, the time-of-use (TOU) electricity prices, and different energy consumption rates of the machine. The first objective is to minimize the makespan and the second is to minimize the total energy costs, by considering both the machine utilization and the economic cost. The problem is formulated as an integer programming model. Then, an exact ε -constraint method is adapted to obtain the exact Pareto front. To deal with large scale problems, based on decomposition ideas, two heuristic methods are developed to obtain approximate Pareto fronts. Computational experiments on randomly generated instances show the effectiveness of the methods. A study case of a real-world glass manufacturing company is also conducted to show that the proposed methods are promising for practical usages. Highlights: A bi-objective single machine batch scheduling problem with energy consideration is studied. An exact epsilon-constraint method is adapted to obtain the exact Pareto front. Two constructive heuristic methods are proposed with the idea of two-stage separations. Performance of the methods is validated by computational experiments and a case study.