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Mathematical Problems in Engineering
Volume 2015 (2015), Article ID 184643, 10 pages
Research Article

A Modified Biogeography-Based Optimization for the Flexible Job Shop Scheduling Problem

School of Electrical Engineering, Shanghai Dianji University, Shanghai 200240, China

Received 20 May 2015; Accepted 28 September 2015

Academic Editor: George S. Dulikravich

Copyright © 2015 Yuzhen Yang. 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.


The flexible job shop scheduling problem (FJSSP) is a practical extension of classical job shop scheduling problem that is known to be NP-hard. In this paper, an effective modified biogeography-based optimization (MBBO) algorithm with machine-based shifting is proposed to solve FJSSP with makespan minimization. The MBBO attaches great importance to the balance between exploration and exploitation. At the initialization stage, different strategies which correspond to two-vector representation are proposed to generate the initial habitats. At global phase, different migration and mutation operators are properly designed. At local phase, a machine-based shifting decoding strategy and a local search based on insertion to the habitat with best makespan are introduced to enhance the exploitation ability. A series of experiments on two well-known benchmark instances are performed. The comparisons between MBBO and other famous algorithms as well as BBO variants prove the effectiveness and efficiency of MBBO in solving FJSSP.