Sustainable fuzzy rough multi-objective multi-route cold transportation model with traffic flow and route constraints

Refrigerated transportation is a reputed worldwide preservation technique for perishables but not always a pollution free mean of transport. Most of the countries, including India employ environmentally unsustainable diesel-based cooling system throughout the entire distribution time. So, this paper proposes two sustainable multi-objective binary linear programming transportation models for fully diesel-based refrigerated trucks and for diesel refrigerated trucks with electric plug-in. Other than the vehicles’ running time, the models consider additional time components notably precooling time, traffic idling time, resting time that are unavoidable during cold transit. Route constraint is also added in the models to choose the optimum route from the multiple transport routes. Traffic flow between each route is considered as one of the objectives along with the operating expenses and distribution time and they are taken to be triangular fuzzy rough numbers to handle real-life uncertainty. The data of sea fish is taken for case study and the put forward models are solved using existing methods of multiobjective optimization like Fuzzy Goal Programming and Weighted Fuzzy Goal Programming in LINGO (19.0). The results are compared to highlight the conveyance that offers better operational efficiency and favours environmental sustainability.