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Mathematical Problems in Engineering
Volume 2017 (2017), Article ID 7249876, 12 pages
https://doi.org/10.1155/2017/7249876
Research Article

A New Energy-Aware Flexible Job Shop Scheduling Method Using Modified Biogeography-Based Optimization

School of Information, Zhejiang University of Finance and Economics, Hangzhou 310018, China

Correspondence should be addressed to Wenyu Zhang; gs.ude.utn.e@gnahzyw

Received 22 May 2017; Accepted 19 July 2017; Published 22 August 2017

Academic Editor: Thomas Hanne

Copyright © 2017 Hua Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Industry consumes approximately half of the total worldwide energy usage. With the increasingly rising energy costs in recent years, it is critically important to consider one of the most widely used energies, electricity, during the production planning process. We propose a new mathematical model that can determine efficient scheduling to minimize the makespan and electricity consumption cost (ECC) for the flexible job shop scheduling problem (FJSSP) under a time-of-use (TOU) policy. In addition to the traditional two subtasks in FJSSP, a new subtask called speed selection, which represents the selection of variable operating speeds, is added. Then, a modified biogeography-based optimization (MBBO) algorithm combined with variable neighborhood search (VNS) is proposed to solve the biobjective problem. Experiments are performed to verify the effectiveness of the proposed MBBO algorithm for obtaining an improved scheduling solution compared to the basic biogeography-based optimization (BBO) algorithm, genetic algorithm (GA), and harmony search (HS).