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All Journal Mandalika Mathematics and Educations Journal
Teppa, Dhirga Tandi
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Mathematics

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Evaluating Swarm-Genetics for VRPTW: Robustness Across Seeds and Fleet Efficiency On Solomon Benchmarks Resky, Aprizal; Zaitun, Zaitun; Teppa, Dhirga Tandi
Mandalika Mathematics and Educations Journal Vol 7 No 4 (2025): Desember
Publisher : FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jm.v7i4.10213

Abstract

The Vehicle Routing Problem with Time Windows (VRPTW) is a challenging NP-hard problem in logistics optimization. This study evaluates a Swarm-Genetics algorithm, a hybrid method combining Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) with swarm regeneration and adaptive parameter control. The algorithm was tested on 57 Solomon benchmark instances (C, R, RC) under three random seeds to assess robustness. Results show that the algorithm is robust across seeds, producing stable outcomes with minimal variation. It frequently preserves fleet efficiency, often matching the Best Known Solutions (BKS) in vehicle count, particularly for clustered instances. However, routing distances remain less competitive, with average gaps of about 10% for clustered, 12–13% for random, and over 20% for mixed cases. Convergence analysis further indicates rapid early improvements but stagnation in complex distributions. Overall, Swarm-Genetics provides a robust and fleet-efficient framework, though further enhancements are needed to improve distance quality.
Co-Authors Resky, Aprizal Zaitun Zaitun