Enhancing the Performance of Biogeography-Based Optimization in Discrete Domain

Oppositional Biogeography-Based Optimization using the Current Optimum (COOBBO) has been recently developed to solve combinatorial problems and outperforms other heuristic algorithms. The objective of this paper is mainly to ascertain various modified methods which can significantly enhance the performance and efficiency of COOBBO algorithm. The improvement measures include crossover approach, local optimization approach and greedy approach. Experiment results illustrate that, the combination model of “inver-over crossover + 2-opt local optimization + all greedy” may be the best choice of all when considering both the overall algorithm performance and computation overhead.

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