Study On Optimizing Emergency Supply Distribution Under Uncertain Environment

These years, natural disasters have occurred sometimes all over the world, and China isone of the few countries that are affected by natural disasters seriously. In China, disasters,such as earthquake, typhoon and mud-rock flow, almost occur every year, which alwaysthreaten people’s life and property safety and seriously influence the growth of Chineseeconomy and the rising of the people’s living standard. Practices have proven that an efficientsystem of emergency supplies distribution can reduce the losses of people’s lives and propertygreatly, which are caused by all kinds of natural disasters. Thus, it is important for us to makeemergency preplans so that emergency supplies can be delivered to disaster areas the firsttime once a disaster occurred. So many scholars at home and abroad have studied a lot in thisfield and these research achievements have helped government and related department a lot torespond to natural disasters. However, most of the research is limited on theoretical level andcertain environment; in fact, the problems that need to be solved often have uncertainvariables, such as transportation time, routing risk and so on.Aiming at the existing problems above, the emergency supplies distribution problemunder uncertain environment is studied in this paper. At first, some research by many scholarsat home and abroad is shown, and the current research status is analyzed. Secondly, this paperintroduces the related concepts of emergency logistic, distinguishes commercial logistics fromemergency logistics, and studies the process of emergency material dispatching. Thirdly, theconcept and characteristic of the risk of transportation are given, and the risk evaluationmodel of emergency supplies distribution problem is set up. Then we describe emergencysupplies distribution problem and set up chance constrained programming models anddependent-chance programming models of emergency supplies distribution problem underfuzzy and random environment, respectively. In order to solve the models, this paper designsa hybrid intelligent algorithm based on simulation techniques and genetic algorithm. Finally,we give an example to prove that the models and the algorithm are correct and feasible. Thesimulation results show that we can apply the models and the algorithm designed in this paperto solve practical problems and select an optimal path; in the future, the research result in thispaper can help the government and relevant decision-making departments to select an optimalpath for emergency supplies distribution problem.