Abstract | ||
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In this paper, the hybridization of PS (Pattern Search) method and SA (Simulated Annealing) are incorporated in the optimization process. This is in order to look for the global optimal solution for the fitness function and decision variables as well as minimum computational CPU time. The real strength of SA approach has been tested in a case study problem of industrial production planning. This is due to the great advantage of SA for being easily escaping from trapped in local minima by accepting up-hill move through a probabilistic procedure in the final stages of optimization process. In the Ph.D. Thesis by Vasant (2008) [4], 16 different techniques were provided of heuristic and meta-heuristic approaches in solving industrial production problems with nonlinear cubic objective functions, eight decision variables and 29 constraints. In this paper, fuzzy technological problems have been solved using hybrid techniques of pattern search and simulated annealing (HSAPS). The simulated and computational results are compared to other various evolutionary techniques. |
Year | DOI | Venue |
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2010 | 10.1016/j.camwa.2010.03.063 | Computers & Mathematics with Applications |
Keywords | Field | DocType |
optimal solution,minimum computational cpu time,industrial production problem,industrial production planning,decision variable,hybrid pattern search,pattern search,fuzzy technological coefficients,simulated annealing,sa approach,computational result,ph.d. thesis,cubic objective function,optimization process,fuzzy production planning problem,industrial production,fitness function,local minima,global optimization,objective function | Simulated annealing,Hill climbing,Heuristic,Mathematical optimization,Adaptive simulated annealing,Fitness function,Production planning,Line search,Mathematics,Pattern search | Journal |
Volume | Issue | ISSN |
60 | 4 | Computers and Mathematics with Applications |
Citations | PageRank | References |
11 | 0.65 | 18 |
Authors | ||
2 |
Name | Order | Citations | PageRank |
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P. Vasant | 1 | 100 | 15.00 |
N. Barsoum | 2 | 16 | 1.53 |