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2 Foundations of Computing and Decision Sciences

2 2022

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

Budi Hendrik Setia, Elveny Marischa, Zhuravlev Pavel, Jalil Abduladheem Turki, Al-Janabi Samaher, Alkaim Ayad F., Saleh Marwan Mahmood, Shichiyakh Rustem Adamovich, Sutarto

Foundations of Computing and Decision Sciences

2022

Vol. 47, No. 2

111--125

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.

A New Model for Scheduling Operations in Modern Agricultural Processes

Noer Zulhery, Elveny Marischa, Jalil Abduladheem Turki, Iswanto A. Heri, Al-Janabi Samaher, Alkaim Ayad F., Mullagulova Gulnara, Nikolaeva Natalia, Shichiyakh Rustem Adamovich

Foundations of Computing and Decision Sciences

2022

Vol. 47, No. 2

151--161

In recent years, the increase in population and the decrease in agricultural lands and water shortages have caused many problems for agriculture and farmers. That is why scheduling is so important for farmers. Therefore, the implementation of an optimal schedule will lead to better use of agricultural land, reduce water consumption in agriculture, increase efficiency and quality of agricultural products. In this research, a scheduling problem for harvesting agricultural products has been investigated. InPaper this problem, there are n number of agricultural lands that in each land m agricultural operations are performed by a number of machines that have different characteristics. This problem is modeled as a scheduling problem in a flexible workshop flow environment that aims to minimize the maximum completion time of agricultural land. The problem is solved by programming an integer linear number using Gams software. The results show that the proposed mathematical model is only capable of solving small and medium-sized problems, and due to the Hard-NP nature of the problem, large-scale software is not able to achieve the optimal solution.