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All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Xin Ying, Felicia Lim
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Computer Science & IT Engineering

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Journal : Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)

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Benchmarking Metaheuristic Algorithms Against Optimization Techniques for Transportation Problem in Supply Chain Management Xin Ying, Felicia Lim; Sufahani, Suliadi Firdaus
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 3 (2025): June 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i3.6513

Abstract

The optimization of transportation problems plays a significant role in supply chain management (SCM), where minimizing costs and improving efficiency are mandatory. The transition from manual methods to advanced computational approaches, such as metaheuristic algorithms, enhances decision-making and consolidates operations within SCM. Malaysia's transportation system has been confronting crucial challenges, characterized by congested roadways, limited rail connectivity and inefficient port operations, which interfere with the fluidity of goods and supply chain efficiency. This highlights the critical need for optimization techniques to enhance competitiveness and efficiency in the evolving SCM landscape. The research aims to explore the application of metaheuristic algorithms, with the Modified Distribution (MODI) method as the benchmark while employing the NorthWest Corner Method (NWCM) to obtain an initial feasible solution, to evaluate their performance in optimizing transportation problems. Metaheuristic algorithms, specifically Simulated Annealing (SA) and Particle Swarm Optimization (PSO), are implemented to explore alternative near-optimal solutions and assess the performance in terms of cost accuracy and computational efficiency. The results indicate that SA achieves a deviation of 12.92% in cost accuracy compared to the optimal MODI method, making it suitable for scenarios where precision is critical, whereas PSO which is 296.92 seconds faster, is ideal for time-sensitive applications. Finally, this study encourages future studies to explore additional algorithms, external factors and broader applications for enhanced real-world relevance and scalability to accentuate the potential of metaheuristic algorithms.
Co-Authors Sufahani, Suliadi Firdaus