Integrated algorithms for network optimization of dangerous goods transportation

Abstract

Network Optimization of Dangerous Goods Transportation (NODGT) belongs to a class of problems referred to as NP-Hard, and strict constraint of it and then make it harder to solve. Considering the capacity of the road network and the maximum expected risk limits, a network optimization model to minimize the total cost was established based on the network flow theory. Improvement on flow distribution model was adopted on the basis of former algorithm. In order to dealing with NODGT, improved algorithms were devised. Furthermore, the problem had been discussed with integrated use of immune cloning algorithm and LINGO. An example was analyzed to demonstrate the correctness of the application. It was proved that improved algorithms were efficient and feasible in solving NODGT.