Multi-Site Aggregate Production Planning Using Particle Swarm Optimization

Aji Prasetya Wibawa; Wayan F. Mahmudy; Agung Mustika Rizki; Gusti Eka Yuliastuti; Ishardita Pambudi Tama

doi:10.32738/JEPPM-2022-0006

Multi-Site Aggregate Production Planning Using Particle Swarm Optimization

Aji Prasetya Wibawa^*
, Wayan F. Mahmudy
, Agung Mustika Rizki
, Gusti Eka Yuliastuti
, Ishardita Pambudi Tama

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

8 Citations (Scopus)

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 multioptimization 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.

Original language	English
Pages (from-to)	62-69
Number of pages	8
Journal	Journal of Engineering, Project, and Production Management
Volume	12
Issue number	1
DOIs	https://doi.org/10.32738/JEPPM-2022-0006
Publication status	Published - Jan 2022

Keywords

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

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10.32738/JEPPM-2022-0006

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title = "Multi-Site Aggregate Production Planning Using Particle Swarm Optimization",

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 multioptimization 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, optimization, particle swarm optimization (PSO), production planning",

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year = "2022",

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doi = "10.32738/JEPPM-2022-0006",

language = "English",

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T1 - Multi-Site Aggregate Production Planning Using Particle Swarm Optimization

AU - Wibawa, Aji Prasetya

AU - Mahmudy, Wayan F.

AU - Rizki, Agung Mustika

AU - Yuliastuti, Gusti Eka

AU - Tama, Ishardita Pambudi

PY - 2022/1

Y1 - 2022/1

N2 - 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 multioptimization 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.

AB - 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 multioptimization 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.

KW - Multi-site aggregate

KW - optimization

KW - particle swarm optimization (PSO)

KW - production planning

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M3 - Article

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JO - Journal of Engineering, Project, and Production Management

JF - Journal of Engineering, Project, and Production Management

IS - 1

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Multi-Site Aggregate Production Planning Using Particle Swarm Optimization

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Keywords

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