Enhancing decision-making in multi-objective fractional transportation problems : A neutrosophic goal programming framework

This study presents an innovative solution for the optimization of Multi-Objective Fractional Transportation Problems (MOFTP) which is a key challenge in modern logistics and supply chain management. This study proposes a pioneering solution by integrating Neutrosophic Goal Programming (NGP) into the MOFTP framework, offering a substantial methodology that accommodates the complexity and uncertainty implicit in transportation systems. The integration of NGP and specified weights enables the consideration of multiple objectives simultaneously while addressing the partial nature of transport parameters. Through simulations and case studies, the effectiveness of the proposed approach is demonstrated, showcasing its ability to provide well-balanced solutions that align with decision-makers strategic objectives.

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Publication Details

Journal
Journal of Information and Optimization Sciences
Published
2025-01-01
DOI
https://doi.org/10.47974/jios-1795
Primary Topic
Optimization and Mathematical Programming
Type
article
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article

Enhancing decision-making in multi-objective fractional transportation problems : A neutrosophic goal programming framework

Priya Agarwal, Vishwas Deep Joshi
Journal of Information and Optimization Sciences
Optimization and Mathematical Programming
article

Enhancing decision-making in multi-objective fractional transportation problems : A neutrosophic goal programming framework

Priya Agarwal, Vishwas Deep Joshi
article en

Abstract

This study presents an innovative solution for the optimization of Multi-Objective Fractional Transportation Problems (MOFTP) which is a key challenge in modern logistics and supply chain management. This study proposes a pioneering solution by integrating Neutrosophic Goal Programming (NGP) into the MOFTP framework, offering a substantial methodology that accommodates the complexity and uncertainty implicit in transportation systems. The integration of NGP and specified weights enables the consideration of multiple objectives simultaneously while addressing the partial nature of transport parameters. Through simulations and case studies, the effectiveness of the proposed approach is demonstrated, showcasing its ability to provide well-balanced solutions that align with decision-makers strategic objectives.

Journal of Information and Optimization SciencesVol. 46(3)
Openalex Percentile: Top 93%
Optimization and Mathematical Programming
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