Multi-Objective Optimization Based on Brain Storm Optimization Algorithm

In recent years, many evolutionary algorithms and population-based algorithms have been developed for solving multi-objective optimization problems. In this paper, the authors propose a new multi-objective brain storm optimization algorithm in which the clustering strategy is applied in the objective space instead of in the solution space in the original brain storm optimization algorithm for solving single objective optimization problems. Two versions of multi-objective brain storm optimization algorithm with different characteristics of diverging operation were tested to validate the usefulness and effectiveness of the proposed algorithm. Experimental results show that the proposed multi-objective brain storm optimization algorithm is a very promising algorithm, at least for solving these tested multi-objective optimization problems.

[1]  Yuhui Shi,et al.  Brain Storm Optimization Algorithm for Multi-objective Optimization Problems , 2012, ICSI.

[2]  Rui Xu,et al.  Survey of clustering algorithms , 2005, IEEE Transactions on Neural Networks.

[3]  Yuhui Shi,et al.  Predator–Prey Brain Storm Optimization for DC Brushless Motor , 2013, IEEE Transactions on Magnetics.

[4]  Daniel Merkle,et al.  A New Multi-objective Particle Swarm Optimization Algorithm Using Clustering Applied to Automated Docking , 2005, Hybrid Metaheuristics.

[5]  M. N. Vrahatis,et al.  Particle swarm optimization method in multiobjective problems , 2002, SAC '02.

[6]  Lothar Thiele,et al.  Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach , 1999, IEEE Trans. Evol. Comput..

[7]  Epaminondas Kapetanios,et al.  On the Notion of Collective Intelligence: Opportunity or Challenge? , 2010, Int. J. Organ. Collect. Intell..

[8]  Nariaki Nishino,et al.  Transdisciplinary Approach to Service Design Based on Consumer's Value and Decision Making , 2010, Int. J. Organ. Collect. Intell..

[9]  Lothar Thiele,et al.  Comparison of Multiobjective Evolutionary Algorithms: Empirical Results , 2000, Evolutionary Computation.

[10]  Thillainathan Logenthiran,et al.  Demand Side Management in Smart Grid Using Heuristic Optimization , 2012, IEEE Transactions on Smart Grid.

[11]  Gary G. Yen,et al.  A Culture-Based Particle Swarm Optimization Framework for Dynamic, Constrained Multi-Objective Optimization , 2012, Int. J. Swarm Intell. Res..

[12]  Yuhui Shi,et al.  Brain Storm Optimization Algorithm with Modified Step-Size and Individual Generation , 2012, ICSI.

[13]  Marco Dorigo,et al.  Ant system: optimization by a colony of cooperating agents , 1996, IEEE Trans. Syst. Man Cybern. Part B.

[14]  Carlos A. Coello Coello,et al.  Evolutionary multi-objective optimization: a historical view of the field , 2006, IEEE Comput. Intell. Mag..

[15]  Bijaya K. Panigrahi,et al.  Brain Storming Incorporated Teaching-Learning-Based Algorithm with Application to Electric Power Dispatch , 2012, SEMCCO.

[16]  Peter J. Fleming,et al.  Genetic Algorithms for Multiobjective Optimization: FormulationDiscussion and Generalization , 1993, ICGA.

[17]  Joel N. Morse,et al.  Reducing the size of the nondominated set: Pruning by clustering , 1980, Comput. Oper. Res..

[18]  Russell C. Eberhart,et al.  Multiobjective optimization using dynamic neighborhood particle swarm optimization , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

[19]  Manoj Kumar Tiwari,et al.  Multiobjective Particle Swarm Algorithm With Fuzzy Clustering for Electrical Power Dispatch , 2008, IEEE Transactions on Evolutionary Computation.

[20]  P. Fleming,et al.  Convergence Acceleration Operator for Multiobjective Optimization , 2007, IEEE Transactions on Evolutionary Computation.

[21]  Kevin M. Passino,et al.  Bacterial Foraging Optimization , 2010, Int. J. Swarm Intell. Res..

[22]  Carlos A. Coello Coello,et al.  Evolutionary multiobjective optimization using a cultural algorithm , 2003, Proceedings of the 2003 IEEE Swarm Intelligence Symposium. SIS'03 (Cat. No.03EX706).

[23]  Konstantinos E. Parsopoulos,et al.  MULTIOBJECTIVE OPTIMIZATION USING PARALLEL VECTOR EVALUATED PARTICLE SWARM OPTIMIZATION , 2003 .

[24]  H. T. Jadhav,et al.  Brain storm optimization algorithm based economic dispatch considering wind power , 2012, 2012 IEEE International Conference on Power and Energy (PECon).

[25]  Carlos A. Coello Coello,et al.  Evolutionary Multi-Objective Optimization in Finance , 2007 .

[26]  Richard Chbeir,et al.  Intelligent and Knowledge-Based Computing for Business and Organizational Advancements , 2012 .

[27]  Min Chen.  Temporal-Based Video Event Detection and Retrieval , 2012, Int. J. Organ. Collect. Intell..

[28]  Tshilidzi Marwala,et al.  Computational Intelligence in Used Products Retrieval and Reproduction , 2013, Int. J. Swarm Intell. Res..

[29]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[30]  Carlos A. Coello Coello,et al.  Using Clustering Techniques to Improve the Performance of a Multi-objective Particle Swarm Optimizer , 2004, GECCO.

[31]  Zhi-hui Zhan,et al.  A modified brain storm optimization , 2012, 2012 IEEE Congress on Evolutionary Computation.

[32]  Anil K. Jain.  Data clustering: 50 years beyond K-means , 2010, Pattern Recognit. Lett..

[33]  C. Fonseca,et al.  GENETIC ALGORITHMS FOR MULTI-OBJECTIVE OPTIMIZATION: FORMULATION, DISCUSSION, AND GENERALIZATION , 1993 .

[34]  Yuhui Shi,et al.  Brain Storm Optimization Algorithm , 2011, ICSI.

[35]  Yaochu Jin,et al.  Dynamic Weighted Aggregation for evolutionary multi-objective optimization: why does it work and how? , 2001 .

[36]  So-Youn Park,et al.  Improvement of a multi-objective differential evolution using clustering algorithm , 2009, 2009 IEEE International Symposium on Industrial Electronics.

[37]  Xin Yao,et al.  Evolutionary programming made faster , 1999, IEEE Trans. Evol. Comput..

[38]  Kalyanmoy Deb,et al.  Muiltiobjective Optimization Using Nondominated Sorting in Genetic Algorithms , 1994, Evolutionary Computation.

[39]  Yuhui Shi,et al.  An Optimization Algorithm Based on Brainstorming Process , 2011, Int. J. Swarm Intell. Res..

[40]  Michael N. Vrahatis,et al.  Particle Swarm Optimization and Intelligence: Advances and Applications , 2010 .