Acta Informatica Malaysia (AIM)

IMPLEMENTATION OF PARTICLE SWARM OPTIMIZATION ALGORITHM IN CROSS-DOCKING DISTRIBUTION PROBLEM

ABSTRACT

IMPLEMENTATION OF PARTICLE SWARM OPTIMIZATION ALGORITHM IN CROSS-DOCKING DISTRIBUTION PROBLEM

Journal: Acta Informatica Malaysia (AIM)
Author: Samuel Ro Paian Purba, Harummi Sekar Amarilies, Nur Layli Rachmawati, A.A.N Perwira Redi

This is an open access article distributed under the Creative Commons Attribution License CC BY 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Doi:10.26480/aim.01.2021.16.20

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 Cross-docking 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.

Pages 16-20
Year 2021
Issue 1
Volume 5

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