Eco-friendly long-haul perishable product transportation with multi-compartment vehicles

Abstract

Multi-compartment refrigerated vehicles (MCVs) have been recently utilized in long-haul perishable product transportation, thanks to their flexibility in storage capacity with different temperature settings. To better understand trade-offs between economic and environmental aspects of long-haul transportation of perishable products with refrigerated vehicles, a Multi-Compartment Vehicle Loading and Scheduling Problem (MCVLSP) that minimizes three objectives—transportation cost, carbon emissions, and total food loss—is herein solved by mathematical modeling and genetic algorithm (GA) approaches. Our computational results indicate that larger MCVLSP instances cannot be solved to optimality using the mathematical model with off-the-shelf optimization software packages. The proposed GA delivers strong computational performance for MCVLSP with respect to solution quality and computational time. We find that, among three objectives, the environmental objective is the most sensitive one as slight difference in either vehicle loading or scheduling decisions could result in solutions with significantly varying carbon emissions. Moreover, solutions with fewer MCVs are not necessarily environmentally sustainable. Rather, deploying larger MCV fleets could potentially result in lower carbon emissions and food weight loss for perishable products—albeit a slight increase in total transportation cost—due to the changes in vehicle loading and scheduling decisions.