Article
Title: "Development of an Adaptive Genetic Algorithm to Optimize the Problem of Unequal Facility Location"
Authors: Hendrik Setia Budi, Marischa Elveny, Pavel Zhuravlev, Abduladheem Turki Jalil, Samaher Al-Janabi, Ayad F. Alkaim, Marwan Mahmood Saleh, Rustem Adamovich Shichiyakh, Sutarto
Pages: 111-125
DOI: 10.2478/fcds-2022-0006
Abstract:

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.

Open access to full text at De Gruyter Online