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040 _cUPMin
041 _aeng
090 0 _aLG993.5 2010
_bA64 P35
100 _aPalma, Hananeel P.
_92162
245 _aParticle swarm optimization for an uncapacitated facility location problem /
_c Hananeel P. Palma
260 _c2010
300 _a53 leaves.
502 _aThesis (BS Applied Mathematics) -- University of the Philippines Mindanao, 2010
520 3 _aThe uncapacitated facility location problem (FLP) is a mathematical way to optimally locate facilities within a set of candidates such that each facility has no capacity limit in satisfying the requirements of a given set of clients. Particle swarm optimization (PSO) is a population-based optimization technique which operates on a population of potential solutions applying an information sharing approach to produce better and better approximations to a solution. Though hybrid methods have been reported to produce better results, this study used PSO in a stand-alone mode to determine first its potential in finding solutions for uncapacitated FLP particularly when applied to real world data. First, a successful mapping between the method and the problem was established. Then a minimization fitness function to evaluate the solutions was defined which involves penalty for every violated constraint. Upon implementation of the method for the problem, best parameter values to solve the problem were achieved. Results showed that applying PSO for the problem yielded better facility locations compared to the existing ones. However, although these results showed that PSO is a promising method to solve this particular problem, further studies are still needed to improve the results such as by reducing the values of the parameters to fit the small-scaled search space of the data.
650 1 7 _aFacility location problem
_92163
650 1 7 _aParticle swarm optimation
_92164
650 1 7 _aUncapacitated facility location problem
_92165
658 _aUndergraduate Thesis
_cAMAT200,
_2BSAM
905 _aFi
905 _aUP
942 _2lcc
_cTHESIS
999 _c2463
_d2463