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The Scientific World Journal
Volume 2014, Article ID 672983, 9 pages
http://dx.doi.org/10.1155/2014/672983
Research Article

Hybrid Biogeography-Based Optimization for Integer Programming

College of Electronics and Information Engineering, Tongji University, Shanghai 201804, China

Received 15 January 2014; Accepted 17 March 2014; Published 3 June 2014

Academic Editors: S. Balochian and Y. Zhang

Copyright © 2014 Zhi-Cheng Wang and Xiao-Bei Wu. 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

Biogeography-based optimization (BBO) is a relatively new bioinspired heuristic for global optimization based on the mathematical models of biogeography. By investigating the applicability and performance of BBO for integer programming, we find that the original BBO algorithm does not perform well on a set of benchmark integer programming problems. Thus we modify the mutation operator and/or the neighborhood structure of the algorithm, resulting in three new BBO-based methods, named BlendBBO, BBO_DE, and LBBO_LDE, respectively. Computational experiments show that these methods are competitive approaches to solve integer programming problems, and the LBBO_LDE shows the best performance on the benchmark problems.