Risk Averse Metaheuristic Hybrid Solution Approach to Vehicle Routing Problem of Hazardous Materials Through the Combination of Game Theory and Tabu Search

Because they have become an integral part of our daily lives, large quantities of hazardous materials are produced and transported each year. In most industrial societies, life without hazardous materials has become almost unimaginable. Hazardous materials are defined as substances that, during transportation, have the potential to pose adverse effects or risks to public health, safety, or property due to their quantity or form. In this context, hazardous materials or products include explosives, gases, flammable and oxidizing substances, toxic and infectious materials, as well as radioactive, corrosive substances and their associated hazardous wastes. The safe transportation of hazardous materials is considered a comprehensive and multidimensional issue, influenced by various legal and physical factors, as well as the numerous risks that vehicles may encounter during transit. Increasing environmental awareness of the potential impacts of hazardous material accidents on public health has significantly heightened both academic and institutional interest in this field. This study proposes a risk-averse solution to the hazardous material transportation problem through a model developed by integrating the Tabu Search algorithm with a game theory–based approach. Within the model, the dispatcher aims to minimize the expected loss under the worst possible conditions in the event of a disruption in any link of the distribution network. In this framework, the expected cost determined through Nash equilibrium is evaluated as an effective and practical analytical tool for strategic decision-making in the selection of safe routes for hazardous material transportation.