Multi-Objective Electric Vehicle Transshipment Problem with Battery Swapping Technology Under Fuzzy Environment

Objectives: To evaluate the efficiency of the multi-objective battery-swapping electric vehicle transshipment problem by analyzing the total cost and time involved in the entire distribution process. Methods: A multi-objective battery-swapping electric vehicle transshipment model is formulated and a case study on a food grain company is considered to demonstrate the pertinent nature of this model. Due to real-life uncertainty, Fermatean fuzzy parameters are considered in this model. Existing neutrosophic fuzzy programming and linear weighted sum method have been used to obtain the solutions for the multi-objective transshipment model. Findings: A comparative study has been made for both multi-objective electric vehicle transshipment and multi-objective electric vehicle transportation problems with battery swapping as well as charging technology. Optimum Solutions obtained for the case study by using these two prescribed methods reveal that the multi-objective transshipment problem with battery swapping gives the minimum transportation cost and time than the charging technology. Obtained solutions for multi-objective electric vehicle transshipment problems with battery swapping show a reduction of 7.8% in cost and 11.19% in the charging technology. Meanwhile, obtained solutions for multi-objective electric vehicle transshipment problems show a reduction of 14% in cost and 14.4% in time than the multi-objective transportation problem. Novelty: The efficiency of multi-objective electric vehicle transshipment problems with battery swapping technology under the Fermatean fuzzy environment has not yet investigated in the literature. 2020 Mathematics Subject Classification: 90B06. Keywords: Transshipment problem, Electric vehicle, Battery swapping technology, Fuzzy environment, Multi­objective transshipment problem