Application of a Fuzzy Multi-Objective Defuzzification Method to Solve a Multi-Modal Transportation Problem

Qusay H Khalaf, Khalid Zeghaiton Chaloob
Journal of Production and Industrial Engineering
Volume 6:Issue 1, Jan-June 2025, pp 12-19

Author's Information
Qusay h khalaf1 
Corresponding Author
Lecturer at Falluja University, Iraq .
drqhk000@gmail.com

Khalid zeghaiton chaloob2
2Lecturer at Falluja University, Iraq
Article -- Peer Reviewed
Published online – 30 June 2025

Open Access article under Creative Commons License

Cite this article – Qusay H Khalaf, Khalid Zeghaiton Chaloob,“Application of a Fuzzy Multi-Objective Defuzzification Method to Solve a Multi-Modal Transportation Problem”, Journal of Production and Industrial Engineering, RAME Publishers, Volume 6, Issue 1, pp. 12-19, 2025.
https://doi.org/10.26706/jpie.6.1.20250602

Abstract:

Multi-modal transportation systems are the logistics networks for global economy. Transportation systems are fraught with uncertainties that hinder the traditional deterministic models reaching the optimal performance. The main obstacle for traditional deterministic models is the uncertainties (e.g., fuel prices volatility, inaccurate transit-times prediction, and evolving environmental regulations). This paper proposes a novel method of fuzzy multi-objective defuzzification. It integrates a modified center of gravity (COG) technique with multi-objective linear programming (MOLP) to address the uncertainty challenges. Triangular fuzzy numbers and partitioning to sud-intervals generated crisp solutions to balance conflicting objectives: cost, time, and environmental sustainability. A four transportation-mode used as a case study, achieving 7.5% cost reduction and 9.2% emission reductions. Analysing sensitivity, 15% increase in air freight allocations occurred by prioritizing time and 20% of shipments to rail and sea occurred by emphasizing sustainability shifts. The robustness of the modified method is highlighted by handling imprecise data and dynamic priorities. Further, a scalable framework for sustainable logistics is aligned with global climate action goals.

Index Terms:
Flare system; Material Selection; Sensitivity Analysis; Entropy; SAW; TOPSIS; Onshore; Hydrocarbon industry

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