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Department of Electrical and Computer Engineering, Faculty of Engineering, University of Birjand, Shoukat-Abad, Birjand, Iran.
Abstract
In this paper a new method for Multi-Objective Optimization (MOO) has been proposed based on Central Force Optimization algorithm.Thismethod has been called‘Multi-Objective Central Force Optimization’ algorithm (MOCFO) . MOCFO utilizes the concept of ‘Pareto Optimality’to identify the positions of non-dominated vectors and employs a repository to maintain the positions. The performance of the MOCFO has been evaluated and compared with other optimization techniques which utilize other heuristic algorithms (e.g. particle swarm optimization, and genetic algorithm). The simulation results show that the performance of the proposed MOCFO is comparable to, sometimes better than other MOO techniques.To ensure the true performance of the method presented when opposed with Multi-Objective Optimization Problems, we evaluate it on standard test functions. The final results exhibit the robustness and performance of the so-called method which spans new opportunities of research for the researchers.
Najafzadeh, H., & Zahiri, S. (2013). The central force multi-objective optimization algorithm. Journal of Soft Computing and Information Technology, 2(1), 10-19.
MLA
Hamed Najafzadeh; Seyed-Hamid Zahiri. "The central force multi-objective optimization algorithm". Journal of Soft Computing and Information Technology, 2, 1, 2013, 10-19.
HARVARD
Najafzadeh, H., Zahiri, S. (2013). 'The central force multi-objective optimization algorithm', Journal of Soft Computing and Information Technology, 2(1), pp. 10-19.
VANCOUVER
Najafzadeh, H., Zahiri, S. The central force multi-objective optimization algorithm. Journal of Soft Computing and Information Technology, 2013; 2(1): 10-19.
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