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2 Foundations of Computing and Decision Sciences

2 2023

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Solving a Two-Level Location Problem with Nonlinear Costs and Limited Capacity: Application of Two-Phase Recursive Algorithm Based on Scatter Search

Meirawan Danny, Ahmed Alim Al Ayub, Alazzawi Fouad Jameel Ibrahim, Chetthamrongchai Paitoon, Alkhayyat Ahmed, Utami Ermi, Artemova Elena Igorevna, Bykanova Olga, Kurniady Dedy Achmad, Komariah Aan

Foundations of Computing and Decision Sciences

2023

Vol. 48, No. 3

371--384

This study examines the issue of distribution network design in the supply chain system. There are many production factories and distribution warehouses in this issue. The most efficient strategy for distributing the product from the factory to the warehouse and from the warehouse to the customer is determined by solving this model. This model combines location problems with and without capacity limits to study a particular location problem. In this system, the cost of production and maintenance of the product in the factory and warehouse is a function of its output. This increases capacity without additional costs, and ultimately does not lose customers. This algorithm is a population-based, innovative method that systematically combines answers to obtain the most accurate answer considering quality and diversity. A two-phase recursive algorithm based on a scattered object has been developed to solve this model. Numerical results show the efficiency and effectiveness of this two-phase algorithm for problems of different sizes.

Designing a Mathematical Model to Solve the Uncertain Facility Location Problem Using C Stochastic Programming Method

Chetthamrongchai Paitoon, Sayed Biju Theruvil, Artemova Elena Igorevna, Sharma Sandhir, Oudah Atheer Y., Al-Nussairi Ahmed Kateb Jumaah, Bashar Bashar S., Iswanto A. Heri

Foundations of Computing and Decision Sciences

2023

Vol. 48, No. 3

345--355

Locating facilities such as factories or warehouses is an important and strategic decision for any organization. Transportation costs, which often form a significant part of the price of goods offered, are a function of the location of the plans. To determine the optimal location of these designs, various methods have been proposed so far, which are generally definite (non-random). The main aim of the study, while introducing these specific algorithms, is to suggest a stochastic model of the location problem based on the existing models, in which random programming, as well as programming with random constraints are utilized. To do so, utilizing programming with random constraints, the stochastic model is transformed into a specific model that can be solved by using the latest algorithms or standard programming methods. Based on the results acquired, this proposed model permits us to attain more realistic solutions considering the random nature of demand. Furthermore, it helps attain this aim by considering other characteristics of the environment and the feedback between them.