Decreasing the Hazards in Routing the Gasoline Fuel Distribution with Applying the Improved Strength Pareto Evolutionary Algorithm under Fuzzy Conditions (Case Study: Bushehr Province)

Considering that the transportation of hazardous materials is associated with a very high risk of human, natural and environmental damage, in addition to paying attention to the economic aspects of the routing of hazardous materials, more emphasis should be placed on reducing population and environmental risks. In this research, a multi-objective model was designed for the problem of vehicle routing to distribute gasoline to fuel stations in Bushehr province in fuzzy conditions, and safety considerations were emphasized. Therefore, the goal is to find the shortest route while respecting safety and environmental considerations.
Methods: Fuzzy logic was used to calculate the risk of the route and the amount of pollution emitted by gasoline vehicles, and to examine the routes in the GIS software and the natural environment, as well as to collect experts' opinions in the form of a questionnaire. To weight the types of risks and objective functions, the best-worst fuzzy multi-criteria decision-making method was used, and to solve the proposed model, the evolutionary algorithm based on improved Pareto intensity was used.
Results: Because in many routing models, the assumption of uncertainty of some parameters seems to be an inevitable assumption. The problems of positioning and routing and the optimal allocation of vehicles are one of the important decisions of organizations because with optimal routing and positioning, optimal allocation of vehicles and then determining the optimal number of cars can reduce an important percentage of related costs. The results of this research show that three optimal solutions on the Pareto frontier have been determined according to the three goals of route travel time, route risk, and the amount of environmental pollution caused by fuel distribution for the route. Also, according to the calculation of the optimal weights for each objective function and the calculation of the weighted average for the Pareto optimal solutions, as well as the field investigation of the proposed route in terms of the presence of accident-prone points and the risk of the route, the Pareto optimal solution was first selected as the optimal route.
Conclusions: Finally, by solving the model and applying weights to the objective functions based on the experts' opinions, the optimal route was identified and introduced. In this research, an attempt has been made to examine innovation from three aspects: theoretical, technical and practical gaps, which can be mentioned as the strengths of the current research compared to other research. From a theoretical point of view, it has been tried to carry out a relatively comprehensive study of factors affecting the routing of the distribution of hazardous materials (such as gasoline) to determine the optimal route. Also, from the technical point of view, the current research is innovative by focusing on combining fuzzy logic with a multi-objective SPEA2 algorithm. Finally, it has been tried to reduce the practical vacuum of previous research in this field by developing optimal routes.