Research On Location-Routing Problem For Emergency Logistics Based On Route Capacity Constraint

The location-allocation problem and the vehicle routing problem are considered comprehensively in LRP through an idea of integration. By the research of LRP, we can not only determine the quantity of the service depot, the location and the scope of clients, but also find the optimal transportation plan and vehicle routing, which has important practical significance.The existing researches are mainly about general logistics system, while the LRP in emergency logistics system has seldom been studied. The location-allocation problems and the vehicle routing problem, are still two key problems in the research of optimizing emergency logistics system, as like in general logistics system, and there are usually studied independently. In fact, there are close link between LAP and VRP in emergency logistics system, therefore, it is very necessary to analyze the relationship of the two, and do research about LRP in emergency logistics system based on the concept of integration optimization and management.This paper firstly introduces the existing research about emergency logistics and LRP. Secondly, we look into the based theory of emergency logistics, including the concept, characteristic, key technique, and so on. And then we put forward a LRP model based on route constraint in emergency logistics. According to the particularity of emergency logistics, the time satisfaction in allocating emergent material is taken for target function in the model, the possible traffic condition, the fuzziness of the emergent material quantity in demand point and the constraint of route type are also considered. Because of the complexity of LRP, which is a problem of NP-Hard, the accurate algorithm is highly limited in solving the problem. And the method that divides LRP into location problem and routing problem, does not express the advantage of LRP that regards LAP and VRP as a whole and considers them comprehensively. Therefore, this paper put forward a genetic algorithm which regards LRP as a whole and could effectively solve the model. Lastly, we choose an example to validate the feasibility and the effectiveness of that model.