HYBRID BIOGEOGRAPHY BASED OPTIMIZATION ALGORITHM FOR OPTIMIZATION PROBLEMS

Khug Alam; Wali Khan; Muhammad Asim

Khug Alam Department of Mathematics, Kohat University of Science & Technology, Pakistan.
Wali Khan Department of Mathematics, Kohat University of Science & Technology, Pakistan.
Muhammad Asim Department of Mathematics, Kohat University of Science & Technology, Pakistan.

Keywords: Optimization, Evolutionary Computation, Evolutionary Algorithms & BBO

Abstract

In the last few years and so, Evolutionary Computation (EC) has become a focusing area for research due to the wide application of various developed evolutionary algorithms (EAs) for dealing with different types of optimization and search problem. Biogeography Based Optimization (BBO) is one of the recently newly and efficiently population based techniques. It uses a set of uniformly and randomly generated solutions and optimizes them in order to get a set of optimized solutions in a single simulation run unlike traditional optimization methods. BBO is mainly shares information between species of migration from one island to another island based mathematical model to perform their search process. In this article, Differential Evolution (DE) has been employed in combination with BBO algorithm and as a result we have developed a new hybrid version of BBO called HBBO. Performance of HBBO is examined by 2005 IEEE Conference on Evolutionary Computation (CEC'05) test suite. The suggested algorithm has efficiently tackled most of the test problems as compared to BBO algorithm.