A Novel DE-PSO-DE (DPD) Algorithm for Economic Load Dispatch Problem
This paper presents a hybrid algorithm of two popular heuristics namely Differential Evolution (DE) and Particle Swarm Optimization (PSO) on a tri-population environment. Initially, the whole population (in increasing order of fitness) is divided into three groups – Inferior Group, Mid Group and Sup...
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| Published in | International journal of applied evolutionary computation Vol. 5; no. 4; pp. 59 - 88 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Hershey
IGI Global
01.10.2014
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1942-3594 1942-3608 |
| DOI | 10.4018/IJAEC.2014100105 |
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| Summary: | This paper presents a hybrid algorithm of two popular heuristics namely Differential Evolution (DE) and Particle Swarm Optimization (PSO) on a tri-population environment. Initially, the whole population (in increasing order of fitness) is divided into three groups – Inferior Group, Mid Group and Superior Group. DE is employed in the inferior and superior groups, whereas PSO is used in the mid-group. It is based on the information sharing mechanism of their inherent property to overcome the shortcomings of each other. The proposed method is called DPD as it uses DE-PSO-DE on a population. Two strategies namely Elitism (to retain the best obtained values so far) and Non-redundant search (to improve the solution quality) have been employed in DPD cycle. Out of a total of 64 DPDs, Top 4 DPDs are investigated through CEC2006 constrained benchmark functions. Based on the ‘performance' analysis, best DPD is reported and further used in solving 5 engineering design problems along with economic load dispatch problem in order to confirm further the efficiency of the proposed DPD. |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
| ISSN: | 1942-3594 1942-3608 |
| DOI: | 10.4018/IJAEC.2014100105 |