Optimization of distribution of centers in the supply chain using genetic algorithms

In this paper evolutionary methods, specifically genetic algorithms (GAs), are used to demonstrate the application in the determination of the location of a distribution center (DC) in the supply chain. One case is tested, which is a problem with GOUTTE's constrains beginning with its solution by the traditional method implemented in Lingo. We pretend to show the efficacy of applying GAs in the determination of the nearest solution to the optimum as the advantage of this method. The results are compared with optimization deterministic models implemented in traditional software by presenting another alternative of solution with an approximation to the optimum value and lower computational cost.

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