Multi-objective Solid Green Trans-shipment Problem for Cold Chain Logistics under Fuzzy Environment

Abstract

In response to intense market competition and escalating environmental concern, cold chain logistics company must emphasize the customer satisfaction, preserve product quality, prevent spoilage, and minimize carbon emissions to support environmental sustainability. This paper presents a multi-objective mathematical model addressing the transshipment problem in cold chain logistics, integrating a solar refrigeration system to optimize transportation costs, spoilage rates, shipping times, and greenhouse gas emissions. To ensure realism, all parameters are analyzed within a neutrosophic fuzzy environment. Subsequently, the proposed neutrosophic fuzzy multi objective solid green transshipment model is transformed into a deterministic model utilizing a ranking function. To achieve the Pareto-optimal solution for the model, established methods such as weighted Tchebycheff metrics programming is examined. A numerical example is included to demonstrate the applicability of this model. A comparative analysis is conducted for both the transshipment problem utilizing the solar refrigeration system and the engine-driven refrigeration system. The proposed model demonstrates a decrease in total costs and carbon emissions when compared to the engine-driven refrigeration system.