Risk assessment in the supply chain of hazardous materials with carbon cap and trade mechanism: multi-objective red deer algorithm

Abstract

The sustainable development goals (SDGs) are designed for the prosperity and peace of the people of the world and the planet in the present and especially in the future. One of the main challenges facing hazardous materials (hazmat) of manufacturing and government is the operational decisions related to hazmat. This is because any accident occurring for hazmat can result in irreversible consequences for society. Therefore, according to numbers 3 and 8 in the SDGs, the objectives of this study are to: (1) examine hazmat management in a supply chain and (2) minimize the supply chain costs and the risk caused by hazmat in the network simultaneously. In this study, according to numbers 12 and 13 in the SDGs, the carbon cap and trade mechanism are used to control the amount of carbon emissions in the network. The carbon cap and trade mechanism is one of the most effective techniques to control greenhouse gas emissions in the international community. In this study, a location-inventory-routing problem (LIRP) is investigated by considering the heterogeneous fleet vehicle, in which production decisions are taken into account. A bi-objective mixed-integer linear programming (MILP) model is presented to formulate the problem. The supply chain network of hazmat is divided into two levels: customers, factories, disposal facilities, and intermediate nodes. A multi-objective red deer algorithm (MORDA), as one of the main novelties of this study, is presented, and also its performance is compared with that of the non-dominated sorting genetic algorithm (NSGA-II) and multi-objective particle swarm optimization (MOPSO). Ultimately, three new metrics are presented to investigate the performance of the applied meta-heuristics, and also a new technique is proposed to choose the most reliable solution.