IMPLEMENTATION OF PARTICLE SWARM OPTIMIZATION ALGORITHM IN CROSSDOCKING DISTRIBUTION PROBLEM

Samuel Ro Paian Purba (), Harummi Sekar Amarilies, Nur Layli Rachmawati and Perwira Redi A.A.n
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Samuel Ro Paian Purba: Department of Logistics Engineering, Universitas Pertamina, Indonesia
Harummi Sekar Amarilies: Department of Logistics Engineering, Universitas Pertamina, Indonesia
Nur Layli Rachmawati: Department of Logistics Engineering, Universitas Pertamina, Indonesia
Perwira Redi A.A.n: Industrial Engineering Department - Binus University

Acta Informatica Malaysia (AIM), 2021, vol. 5, issue 1, 16-20

Abstract: In order to increase customer satisfaction and maintain customer loyalty, logistics service providers must pay attention to the quality of service provided, one of which is effecive warehouse management, especially in scheduling the arrival and departure of products transporting vehicles. Therefore, this study discusses warehouse management in form of delivery and pickup scheduling at PT XYZ’s cross-docking warehouse. This study aims to obtain effective delivery and pickup scheduling and minimize operational costs. The Crossdocking Distribution Problem is an np-hard problem, so the Particle Swarm Optimization algorithm is used, which is a metaheuristic method in finding solutions. Based on the result, it was found that effective delivery and pickup scheduling was able to save inventory cost by 3.12% and reduce the percentage of delays from 73% to 0%. The scheduling process using Particle Swarm Optimization requires an average computation time of 26.2 seconds.

Keywords: Delivery; pickup; cross-docking distribution problem; particle swarm optimization. (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:zib:zbnaim:v:5:y:2021:i:1:p:16-20

DOI: 10.26480/aim.01.2021.16.20

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