Multi-objective Multi-route Soft Rough Sustainable Transportation Problem based on Various Road Maintenance Conditions

Published

16-10-2025

DOI:

https://doi.org/10.58414/SCIENTIFICTEMPER.2025.16.10.02

Keywords:

Soft rough transportation problem, Multi-objective, Multi-route, Road maintenance condition, Sustainability

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Issue

Section

Research article

Authors

  • L Brigith Gladys Research Scholar, PG & Research Department of Mathematics, Holy Cross College (Autonomous), Affiliated to Bharathidasan University, Tiruchirappalli-620002, Tamil Nadu, India.
  • J Merline Vinotha Assistant Professor, PG & Research Department of Mathematics, Holy Cross College (Autonomous), Affiliated to Bharathidasan University, Tiruchirappalli-620002, Tamil Nadu, India.

Abstract

A heap of transportation problems is communicated and sorted out everyday yet are not prone to hybrid ambiguity tools like soft rough environment. Soft rough transportation parameters amplify the impreciseness particularly with reference to each decision alternative in the supply chain. The intent of this chapter is to conceive a multi-objective soft rough transportation model with multiple distribution routes. To promote green transportation, a sustainability influencing parameter set namely ‘various maintenance condition of roads’ which contain parameters namely good, moderate and no maintenance is chosen. Meanwhile, transportation cost, International Roughness Index (IRI) of road and carbon emission are contemplated as objectives. Each unique element in the parameter set propounds as a soft rough model that is made deterministic using expected operators and then solved using fuzzy goal programming approach in LINGO (19.0). Numerical examples are furnished to evaluate the soft rough models that look up to the preference of decision makers.
Mathematics Subject Classsifications (2020): 90B06, 90C08

How to Cite

Gladys, L. B., & Vinotha, J. M. (2025). Multi-objective Multi-route Soft Rough Sustainable Transportation Problem based on Various Road Maintenance Conditions. The Scientific Temper, 16(10), 4853–4857. https://doi.org/10.58414/SCIENTIFICTEMPER.2025.16.10.02

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