Recent Developments In Biologically Inspired Computing
Recent Developments In Biologically Inspired Computing
Population distributions in biogeography-based optimization algorithms with elitism
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Biogeography-based optimization combined with evolutionary strategy and immigration refusal
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Biogeography-based optimization and the solution of the power flow problem
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Oppositional biogeography-based optimization
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
A gradient-based artificial immune system applied to optimal power flow problems
ICARIS'07 Proceedings of the 6th international conference on Artificial immune systems
Immune and evolutionary approaches to software mutation testing
ICARIS'07 Proceedings of the 6th international conference on Artificial immune systems
Soft Computing - A Fusion of Foundations, Methodologies and Applications
A probabilistic analysis of a simplified biogeography-based optimization algorithm
Evolutionary Computation
Learning and optimization using the clonal selection principle
IEEE Transactions on Evolutionary Computation
Biogeography-Based Optimization
IEEE Transactions on Evolutionary Computation
Biogeography based optimization for multi-knapsack problems
ISNN'12 Proceedings of the 9th international conference on Advances in Neural Networks - Volume Part I
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The interest of hybridizing different nature inspired algorithms has been growing in recent years. As a relatively new algorithm in this field, Biogeography Based Optimization(BBO) shows great potential in solving numerical optimization problems and some practical problems like TSP. In this paper, we proposed an algorithm which combines Biogeography Based Optimization (BBO) and Clonal Selection Algorithm (BBOCSA). Several benchmark functions are used for comparison among the hybrid and other nature inspired algorithms (BBO, CSA, PSO and GA). Simulation results show that clone selection can enhance the ability of exploration of BBO and the proposed hybrid algorithm has better performance than the other algorithms on some benchmarks.