A Neutrosophic Fixed Charge Multi-Objective 4 Dimensional Multi-item Transportation Problem with Carbon Emission and Budget Constraints

Abstract

This paper seeks to address 4-dimensional transportation challenges by integrating budget con
straints, vehicle speed, carbon emissions, and optimizing for maximum profit and minimum time. The rising
 number of vehicles, varying road conditions, and diverse vehicle types used to meet daily needs have exacerbated
 issues like global warming and greenhouse gas (GHG) emissions. Our goal is to reduce carbon emissions for
 a cleaner environment. Single-objective, single-item transportation systems are often insufficient for scenarios
 with multiple criteria. Thus, we adopt a multi-objective, multi-item decision-making approach to tackle real-life
 transportation problems. Practical challenges frequently involve uncertainties stemming from time pressures,
 insufficient data, information gaps, or inaccuracies in measurement. Recognizing this, we incorporate indeter
minacy in our problem design. To address the uncertainties and ambiguities found in fuzzy and intuitionistic
 fuzzy settings, we utilize a neutrosophic set, which is well-suited to handle such complexities. Consequently, we
 employ neutrosophic linear programming to derive a compromise solution for the proposed neutrosophic fixed
 charge multi-objective, four-dimensional, multi-item transportation problem, considering carbon emissions and
 budget constraints. The model’s effectiveness is showcased using a numerical example, with the results displayed
 and analyzed. Finally, sensitivity analysis and conclusions, along with future research directions, are presented.

DOI:  10.5281/zenodo.14423876