Robust Optimization Of Emergency Vehicle Routing Problem With Uncertain Time

In recent years, many disaster happened all over the world, caused dam-age on not only human society but also economy, bringing us huge economic loss. With latest but insufficient massage, the efficiently rescue is hard for the decision maker, which is regarded as a significant issue to be solved for the whole world in face with the major emergencies.According of the above, combined the characteristic of the emergency logistics,the essay study the vehicle routing problem. For the vital role of the time effectiveness in emergency management, this thesis mainly discussed the vehicle routing problem with less information in the eva of the rescue.And,on the basis of the rescue effect by a single car or all vehicle, we divided the problem into two parts, chance constrain model and joint chance constrain model. From the main part of the thesis we apply the Robust Optimization on the two models, obtain the robust counterpart of the two models, and design the corresponding algorithm. There are details in this thesis:1) After an interview of recent researches of the emergency vehicle routing problem, some existence questions are found and the practical significance of the vehicle scheduling after the emergent events is explained.2)Considering the vehicle routing problem of time requirements and the uncertain time spent on the road, a chance constrained model aimed with min-imizing the time is given. Then we discussed the individual chance constrained vehicle routing model, and obtain the robust counterpart.For the joint chance constrained model on the basis of other people’s research,we use a CVaR function to convex approximate the joint chance constrain, and obtain the ap-proximation algorithm to the concave vehicle touting model based joint chance constrain.3)Finally,we use an example to prove the analysis above and the algorithm are computational tractable.