Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/32539
Title: A modified differential evolution algorithm with fitness sharing for power system planning
Authors: Yang, GY
Dong, ZY
Wong, KP
Keywords: Differential evolution
Evolutionary algorithms
Evolutionary computation
Evolutionary programming
Evolutionary strategy
Genetic algorithms
Issue Date: 2008
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE transactions on power systems, 2008, v. 23, no. 2, p. 514-522 How to cite?
Journal: IEEE transactions on power systems 
Abstract: The application of evolutionary computation methods in search and optimization has been growing over the past few decades. As a promising approach in metaheuristic optimization algorithms, differential evolution (DE) has been attracting increasing attention for wide engineering applications including power engineering. Different from conventional evolutionary algorithms using predefined probability distribution function for mutation process, differential evolution exploits the differences of randomly sampled pairs of objective vectors for its mutation process. Consequently the variation between vectors will outfit the objective functions topographical information toward the optimization process, and therefore provides efficient global optimization capability. However, although DE is shown to be precise, fast as well as robust, its search efficiency will be impaired during solution process with fast descending diversity of population. In this paper, detailed numerical studies are carried out to propose the characterization of the performance of several DE mutation methods with and without fitness sharing scheme. All the approaches using the proposed modified DE are presented on an example in power system planning.
URI: http://hdl.handle.net/10397/32539
ISSN: 0885-8950
EISSN: 1558-0679
DOI: 10.1109/TPWRS.2008.919420
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