Research On Integrated Optimization Model And Algorithm For Location-Inventory-Routing Problem Taking Time Into Consideration

With the globalization and the progress of society, people's demands are more and more variant and stochastic, enterprises have to shorten their product life cycle to meet people's variable demands, which make the market Time-Based Competed. In order to meet people's demands, logistics system as one important part of enterprise has to adjust to the new competition environment inevitably. Facility location, inventory policy, delivery plan are three most key factors which influence logistics system. For these reasons, this paper will research location-inventory-routing problem taking time into consideration.In the first chapter, this paper introduces it's research background,research significance and research situation of home and abroad, indicates that it is necessary to research this topic.In the second chapter, this paper presents three algorithms will be used in the following chapters.In the third chapter, taking time window constraint into consideration, a model of the location-inventory-routing problem with soft time window for spare parts logistics system is established. And a two phase hybrid heuristic algorithm based on taboo search and improved C-W algorithm is presented to solve the model. The first phase is to solve the location inventory problem, the second one is to settle the vehicle routing problem with soft time window, taboo search algorithm is used to improve the solution until get the last solution.In the fourth chapter, Given the importance of order cycle to logistics system cost, this paper introduces it into model as a decision variable, and build a model of location-inventory-routing problem based on it. A hybrid heuristic algorithm based on lagrangian relaxation algorithm and taboo search algorithm is put forward to solve the model. The algorithm have 3 steps:Firstly, dividing the model into two subproblems by lagrangian relaxation algorithm; Secondly, solving each of the two subproblems and get the initial solution; Finally, using taboo search algorithm to improve the solution until get the last solution.All the models and algorithms in the above chapters are confirmed to be feasible through examples.In the fifth chapter, we summarize this paper and put forward the direction of improving.