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An Efficient Evolutionary Optimization Algorithm for Multiobjective

Taher Niknam and Mokhtar Sha Sadeghi
International Journal of Control, Automation, and Systems, vol. 9, no. 1, pp.112-117, 2011

Abstract : In this paper, a Multi-objective Modified Honey Bee Mating Optimization (MMHBMO) evolutionary algorithm is proposed to solve the multi-objective Distribution Feeder Reconfiguration (DFR). The real power loss, the number of the switching operations and the deviation of the voltage at each node are considered as the objective functions. Conventional algorithms for solving the multi-objective optimization problems convert the multiple objectives into a single objective using a vector of the user-predefined weights. This paper presents a new MHBMO algorithm for the DFR problem. In the pro-posed algorithm an external repository is utilized to save non-dominated solutions found during the search process. A fuzzy clustering technique is used to control the size of the repository within the limits because of the objective functions are not the same. The proposed algorithm is tested on a distribution test feeder.

Keyword : Distribution feeder reconfiguration, evolutionary algorithm, modified honey bee mating optimization (MHBMO), multi-objective optimization.

 
 
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