Improved ant colony optimization for multi-objective route planning of dangerous goods

Dangerous goods (DGs) can significantly affect the human and nature if they are exposed to the environment without any protection. This situation is likely to occur when accidents happen during the transportation process. Especially in large cities, due to high population density and complex traffic network, the transportation of GDs has to pass through densely populated areas or other sensitive districts. So only considering one traditional objective in routing planning, such as the shortest length of route or lowest cost, can no longer meet our needs. There is an urgent need to review and improve the way of route optimization for DGs transportation. This paper develops a multi-objective model for the determination of optimal routes. In this model, three conflicting objectives are considered. They are total travelling time, accident probability and population exposure risk. For settling this model, an improved ant colony optimization (ACO) is introduced with a novel multi-objective decision method named MAXMIN. With the support of geographical information system (GIS), a case study of Hong Kong is carried out for the transportation of DGs. The experimental results show the proposed approach is feasible and effective.