(24c) Optimum Route Selection for Hazardous Materials Transportation Incorporating Security and Cost-Effectiveness Considerations | AIChE

(24c) Optimum Route Selection for Hazardous Materials Transportation Incorporating Security and Cost-Effectiveness Considerations

Authors 

Qiao, A. - Presenter, Det Norske Veritas (U.S.A.), Inc.
Keren, N. - Presenter, Iowa State University
Mannan, D. M. S. - Presenter, Texas A&M University


The routing of hazardous materials shipments has become an issue of major importance and thus an active area of research due to the increasing public awareness of the potential risks associated with the hazardous materials transportation. This paper presents a new routing model based on security and cost analysis that decision makers from both industry and government can use to solve hazardous materials logistical problems.

The optimal route for hazardous materials transportation is obtained from the network ?minimum cost flow? model with input variables of transportation cost and potential risk. Both of the inputs are decided by various parameters describing the nature of the truck configuration, operation, environment, road conditions, and other conditions. Therefore both input variables need to be assessed at first in the hierarchical transportation system to obtain the optimal route.

The transportation risk is assessed by SAFETI, one of the most popular risk analysis packages in the oil and gas industry. Parameters affecting both frequency and consequence are input to SAFETI to derive the risk level of the transportation activity. The transportation cost considers both the operating cost and the potential increase of insurance premium if a transportation accident occurs.

The transportation network is a graph composed by nodes and arcs. The optimal solution, found by solving a 'minimum cost flow problem', is composed by paths in the transportation network, and the paths results in the combination of higher security and lower transportation cost. The security and cost could have different weights in deciding the optimum route. The weights could be defined by users, or derived by fuzzy model based on expertise experience and fuzzy if-then rules. By this way the route selection can be optimized to a higher level since it considered the different importance level of input variables and the requirement of users. The optimum route found by this way provides a basis for management systems in making strategic, tactical and operational decisions.