Journal of Engineering, Project, and Production Management, 2022, 12(1), 62-69


Multi-Site Aggregate Production Planning Using Particle Swarm Optimization


Aji Prasetya Wibawa1, Wayan F. Mahmudy2, Agung Mustika Rizki2, Gusti Eka Yuliastuti2, and Ishardita Pambudi Tama3

1Lecturer, Electrical Engineering Department, Universitas Negeri Malang, Malang, Indonesia. Email: aji.prasetya.ft@um.ac.id (corresponding author).
2Lecturer, Computer Science, Faculty of Computer Science, Brawijaya University, Malang, Indonesia.
3Lecturer, Industrial Engineering, Faculty of Engineering, Brawijaya University, Malang, Indonesia.



Production Management


Received February 22, 2021; revised July 29, 2021; accepted September 10, 2021


Available online October 2, 2021


Abstract: Aggregate planning is a crucial stage in the production process because it supports other processes. Careless production planning may cause production costs to spike sharply that hurts the company financially. This study explores the novel usage of particle swarm optimization (PSO) to discover a set of solutions among the objective of a multi-optimization problem in aggregate production planning. The study uses a small home textile industry with complex production processes of school uniforms as a case study. The results show that the production cost difference between actual data and the proposed method is IDR330,670,000. Thus, PSO can solve the multi-site aggregate planning by reducing the company production cost.


Keywords: Multi-site aggregate, particle swarm optimization (PSO), production planning, optimization

Copyright © Journal of Engineering, Project, and Production Management (EPPM-Journal).

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 Unported License.

Requests for reprints and permissions at eppm.journal@gmail.com.

Citation: Wibawa, A. P., Mahmudy, W. F., Rizki, A. M., Yuliastuti, G. E., and Tama, I. P. (2022). Multi-Site Aggregate Production Planning Using Particle Swarm Optimization. Journal of Engineering, Project, and Production Management, 12(1), 62-69.

DOI: 10.32738/jeppm-2022-0006

Full Text

Copyright © EPPM-Journal. All rights reserved.