PSOLVER: A new hybrid particle swarm optimization algorithm for solving continuous optimization problems

被引:38
|
作者
Kayhan, Ali Haydar [1 ]
Ceylan, Huseyin [1 ]
Ayvaz, M. Tamer [1 ]
Gurarslan, Gurhan [1 ]
机构
[1] Pamukkale Univ, Dept Civil Engn, TR-20070 Denizli, Turkey
关键词
Particle swarm optimization; Hybridization; Spreadsheets; Solver; Optimization; CONTINUOUS ENGINEERING OPTIMIZATION; HARMONY SEARCH ALGORITHM; GENETIC ALGORITHMS; SIMPLEX SEARCH; SPREADSHEET SOLVERS;
D O I
10.1016/j.eswa.2010.03.046
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This study deals with a new hybrid global-local optimization algorithm named PSOLVER that combines particle swarm optimization (PSO) and a spreadsheet "Solver" to solve continuous optimization problems. In the hybrid PSOLVER algorithm, PSO and Solver are used as the global and local optimizers, respectively. Thus, PSO and Solver work mutually by feeding each other in terms of initial and sub-initial solution points to produce fine initial solutions and avoid from local optima. A comparative study has been carried out to show the effectiveness of the PSOLVER over standard PSO algorithm. Then, six constrained and three engineering design problems have been solved and obtained results are compared with other heuristic and non-heuristic solution algorithms. Identified results demonstrate that, the hybrid PSOLVER algorithm requires less iterations and gives more effective results than other heuristic and non-heuristic solution algorithms. (C) 2010 Elsevier Ltd. All rights reserved.
引用
收藏
页码:6798 / 6808
页数:11
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