Application of Plant Growth Simulation Algorithm on Solving Facility Location Problem

Abstract Based on Plant Growth Simulation Algorithm (PGSA), we proposed an intelligence optimization algorithm for solving facility location problems. We comparer the calculating results of PGSA with Genetic Algorithm (GA) for distribution center location problem, and from the result, it was observed that PGSA is better than GA on accuracy. Furthermore, by selecting 50 customers randomly, we solved the Weber multi-facility location problem. Different from other heuristic algorithms, PGSA can find global optimal solutions. Meanwhile, according to the different facility numbers, we combined global and local optimal solutions, set up optimal facility location arrangement as a whole. The algorithm herein shows its accuracy, astringency, and generalization. It is an actual application of PGSA on solving location problems.

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