Study On Stacker Path Optimization Methods Of Fixed Shelf In Automated Warehouse

With the continuous development of modern science, technology and economy, logistics has rapidly growed a new service industry with unlimited potential and development space from the initial concept formation, development and the continuous improvement. The level of development for modern logistics industry is the important symbol of measuring a country's comprehensive national strength and is gaining each national attention. Therefore, accelerating the development of modern logistics industry is of great significance for exploring new economic growth and improving the internationalization, information and market of urban economy.With the continuous expanding and deepening of the production scale of enterprise modernization, automated warehouses have become an important and indispensable part in the logistics system. As the smallest footprint and best utilization of space, Automated warehouse gradually replaces the obsolete plane warehouse with a low area utilization rate, which promptes warehousing. The operation and management of the automated warehouse demonstrate its efficiency, planning and facility. Therefore, more and more enterprises pay attention to it. From the current technology structure of the automated warehouse, there has been an increasing concern about hardware, automation and communication technologies, but the optimization of management, scheduling and operation for automated warehouse, which is not a completely mature aspect, has not aroused great attention, so the role of automated warehouse is not fully played.Stereo shelf and Roadway-stacker are the important components of the automated warehouse. The efficiency of the material flowing depends on the stacker's efficiency. In addition to the stacker's performance parameters, scheduling is the main factor of its efficiency, so the study on the stacker's operation and scheduling is of very important significance for enhancing the efficiency of the warehouse. In this paper, the application of GA, ACA and TransCAD solves the TSP of the stacker path optimization of automated warehouse fixed shelf and the followings are the main points.Chaper one, Introduction. Introduced the research background, the purpose and significance, research status and development trends in our country and abroad of this thesis.Chaper two, the outline of the automated warehouse. Firstly, a brief developmental situation of the automated warehouse. Secondly, summarized up the four functions of the automated warehouse and analyzed the social and economic benefits which automated warehouse brings to people. Thirdly, classified automated warehouse by seven types. The diversity of its classification enable it to serve in various industries and prompts the development of the automated warehouse.Fourthly, introduced working process about the five systems of the automated warehouse. Finally, detailedly analysed the process and principle of the order picking.Chaper three, analysed the algorithm for TSP. Firstly, introduced the development of GA, basic terms and related concepts, running steps and flow charts, summarized up the characteristics of GA according to comparing with those traditional opitimization methods, the basic operating technology of coding, selection, crossover and mutation. At last, detailedly introduced the origin, theory and mathematical models of ACA.Chaper four, the study on applying of stacker path optimization methods.1. Applying GA solved the TSP of the stacker path optimization.GA can reflect the complicated phenomenon through natural evolutionary mechanisms and not limit to local optimization, so only applied GA to optimize ordering picking. Optimized a picking task containing 19 sites, achieved optimal path and its length, as well as generated convergent charts by Matlab.2. GA combining ACA solved the TSP of the stacker path optimization.When GA solves TSP, random selection of the initial population will choose some poor ones and affect results. Therefore, combined GA and ACA. Selected initial population by ACA and then seeked the optimal solution by GA. Optimized the same task containing 19 sites. GA combining ACA is superior to GA by the solutions. 3. Applying TransCAD solved the TSP of the stacker path optimization.When GA solves the TSP of the stacker path optimization, the optimal solution is only the effective approximate one, as well as computation and program are complicated. So try to apply TransCAD to solve the TSP of the stacker path optimization and optimize a picking task cointaining 5 sites. Not only avoid the complex calculation and tedious program, but also achieve the actual shortest path and its simulation.Chaper five, summary and outlook. Summarized the work of this paper and pointed out some questions which need to be studied on in further.The followings are the novelties of this paper.1. When GA optimize the path of picking, randomly generating two-matrix becomes initial population which is consistent with the basic principle of GA and facilitates the crossover.2. Apply TransCAD to solve the TSP of the stacker's picking path, achieve the actual shortest path and its simulation.