Development of an Adaptive Genetic Algorithm to Optimize the Problem Of Unequal Facility Location

The problem of unequal facility location involves determining the location of a set of production equipment whose dimensions are different, as well as the interrelationships between each of them. This paper presents an efficient method for optimizing the problem of unequal facility layouts. In this method, the genetic algorithm is improved and developed into an adaptive genetic algorithm. In this algorithm, the mutation operator is applied only when the similarity of chromosomes in each population reaches a certain level. This intelligence prevents jumps in situations where they are not needed and reduces computational time. In order to measure the performance of the proposed algorithm, its performance is compared with the performance of conventional genetic algorithms and refrigeration simulators. Computational results show that the adaptive genetic algorithm is able to achieve higher-quality solutions.

Automated summary

This paper proposes an efficient method, called adaptive genetic algorithm, for optimizing the problem of unequal facility layouts. In this algorithm, the mutation operator is applied only when the similarity of chromosomes reaches a certain level, which prevents unnecessary jumps and reduces computational time. Experimental results show that the adaptive genetic algorithm is capable of achieving higher-quality solutions.