Designing Mathematical Routing Model of Hazardous Materials Transportation (Case Study: the Fars Province Road Network)

In most cases, the place of producing and using hazardous materials is not the same and such materials should be transported from the production line to the consumption place. Because of the dangerous nature of such materials, safety indicators and criteria should be considered. More than 90% of hazardous materials transportation in Iran is by road. This shows the importance of attention to the safety factors. Although transportation departments or local governments are responsible for allocating acceptable paths that reduce risk, transportation companies usually look for some paths with lower travel times and fuel consumption. So many methods have been presented for designing the paths of hazardous materials transportation based on the trade -off between costs and risks of the transportation. Almost in all of them the national hazardous materials transport routing has been a decision for the matter in two levels, the government allocates a subset of the transport network to hazardous materials and the transportation corporations, choose their paths from this subset. However, the issue of justice in the distribution of risk is highly regarded in the states because feeling Injustice in received level of risk, might lead to public opposition to the routing of hazardous materials. Therefore in this research some routing models have been proposed. In the first mathematical model, we just consider the safety of paths and two major goals would be pursued. First we seek ways of minimizing risk in the whole studied path networks, and then this matter would be considered that the risk does not increase in each link more than certain amount, and in fact justice in the distribution of risk be established. This model was bi-level linear and transformed into a single-level mixed integer linear program by replacing the second level by its Karush–Kuhn–Tucker conditions and by linearizing the complementary constraints. Then we solve the MIP problem with a commercial optimization solver In the second model, in addition to the safety, the economic efficiency of the routes is considered. In fact, in this model, the results of the safety model will be used in a mathematical model with economic-safety approach. The real case study then has been used to evaluate mathematical In most cases, the place of producing and using hazardous materials is not the same and such materials should be transported from the production line to the consumption place. Because of the dangerous nature of such materials, safety indicators and criteria should be considered. More than 90% of hazardous materials transportation in Iran is by road. This shows the importance of attention to the safety factors. Although transportation departments or local governments are responsible for allocating acceptable paths that reduce risk, transportation companies usually look for some paths with lower travel times and fuel consumption. So many methods have been presented for designing the paths of hazardous materials transportation based on the trade -off between costs and risks of the transportation. Almost in all of them the national hazardous materials transport routing has been a decision for the matter in two levels, the government allocates a subset of the transport network to hazardous materials and the transportation corporations, choose their paths from this subset. However, the issue of justice in the distribution of risk is highly regarded in the states because feeling Injustice in received level of risk, might lead to public opposition to the routing of hazardous materials. Therefore in this research some routing models have been proposed. In the first mathematical model, we just consider the safety of paths and two major goals would be pursued. First we seek ways of minimizing risk in the whole studied path networks, and then this matter would be considered that the risk does not increase in each link more than certain amount, and in fact justice in the distribution of risk be established. This model was bi-level linear and transformed into a single-level mixed integer linear program by replacing the second level by its Karush–Kuhn–Tucker conditions and by linearizing the complementary constraints. Then we solve the MIP problem with a commercial optimization solver In the second model, in addition to the safety, the economic efficiency of the routes is considered. In fact, in this model, the results of the safety model will be used in a mathematical model with economic-safety approach. The real case study then has been used to evaluate mathematical