Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/3124
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
Keywords: : Unequal Facility location
Interactions
Adaptive Genetic Algorithm
Mutation Operator Intelligence,
healthy lifestyle
Issue Date: 2022
Publisher: F O U N D A T I O N S O F C O M P U T I N G A N D D E C I S I O N S C I E N C E S
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.
URI: http://localhost:8080/xmlui/handle/123456789/3124
ISSN: ISSN 0867-6356 e-ISSN 2300-3405
Appears in Collections:قسم الفيزياء الحياتية

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