Two-stage update biogeography-based optimization using differential evolution algorithm (DBBO)

Authors:
Ilhem Boussaïd;Amitava Chatterjee;Patrick Siarry;Mohamed Ahmed-Nacer
Affiliations:
Université des sciences et de la technologie Houari Boumediene, Electrical Engineering and Computer Science Department, El-Alia BP 32 Bab-Ezzouar, 16111 Algiers, Algeria;Jadavpur University, Electrical Engineering Department, Kolkata, West Bengal 700 032, India;Université de Paris-Est Créteil Val de Marne, LiSSi (EA 3956), 61 avenue du Général de Gaulle, 94010 Créteil, France;Université des sciences et de la technologie Houari Boumediene, Electrical Engineering and Computer Science Department, El-Alia BP 32 Bab-Ezzouar, 16111 Algiers, Algeria
Venue:
Computers and Operations Research
Year:
2011

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Abstract

The present paper proposes a new stochastic optimization algorithm as a hybridization of a relatively recent stochastic optimization algorithm, called biogeography-based optimization (BBO) with the differential evolution (DE) algorithm. This combination incorporates DE algorithm into the optimization procedure of BBO with an attempt to incorporate diversity to overcome stagnation at local optima. We also propose to implement an additional selection procedure for BBO, which preserves fitter habitats for subsequent generations. The proposed variation of BBO, named DBBO, is tested for several benchmark function optimization problems. The results show that DBBO can significantly outperform the basic BBO algorithm and can mostly emerge as the best solution providing algorithm among competing BBO and DE algorithms.