Bi-objective vehicle routing problem for hazardous materials transportation

In hazardous materials distribution and recollection, economic, social and environmental aspects need to be considered simultaneously. The stakeholders involved in these activities have different and sometimes conflicting objectives, shippers and carriers are interested in a cost efficient distribution while government and population are interested in a safe transportation. A method for providing trade-off solutions is proposed through the determination of a set of routes that simultaneously minimizes two conflicting objectives, the total routing risk and the total transportation cost. This hazardous materials transportation problem is modeled by vehicle routing problem using a heterogeneous fleet of trucks. The multi-objective version of vehicle routing problem has not been as studied as its mono-objective version. Two solutions methods are proposed, a multi-objective neighborhood dominance-based algorithm and an ε-constraint meta-heuristic algorithm, both of them based on neighborhood search. A comprehensive comparison among the proposed solution methods is carried out using multi-objective metrics. The algorithms are tested on 20 modified benchmark instances (including the risk assessment associated parameters) with up to 100 customers. The results show that the use of the dominance-based algorithm presents a better performance, in terms of the quality of the Pareto front approximation, than the utilization of the ε-constraint method.