Study On Key Technologies Of Container Terminal Auto-Stowage Based On Operation Resources Configuration

Container terminal auto-stowage is a research project which combined withcomputer technology and container terminal operation management technology. As acore part of the supply chain of the container logistics，stowage planning play a key rolein the terminal handling process. However，there are few effective methods to solve thiscomplex multi-constraint problem neither at home nor at abroad.With the developing of shipping business and the enlargement of container vessels’scale，more and more factors will be considered in the traditional manual way of stowage.In such a situation， relying on human experience to deploy cranes， trailers，RTGs andother terminal resources to achieve efficient and accurate stowage is becoming more andmore difficult.Therefore, developing a reasonable and effective intelligent optimization approach tosolve such multi-objective combinatorial optimization problems as a challenge toresearchers,, which not only meets project real-time requirements but also achievesoptimal management of production operations.Based on past researches in computer aided large-scale modern container terminaloperation management application in the early years, this dissertation faces and solvesthe new technical difficulties which encountered in engineering practice. With thepurpose to achieve intelligent and automated stowage, the dissertation can free stowagemembers from heavy mental work.The major research based on resources configuration in container terminal，coversberth planning， ship planning，yard planning and equipment control. Through studyingdynamic configuration of operation resources in container terminal business andinterrelationships between stowage and yard management，this dissertation establish theevaluation system of key indicators of container terminal operation resources，develop three-tier programming mathematical model of intelligent stowage planning and anintegrated system of algorithms., which achieve quick accurate，efficient stowageplanning and a huge boost of container terminal operational level and efficiency.Innovations of the dissertation as follows：Building the three-tier system of models of container terminal auto-stowagebased on operation resources dynamic configuration.This dissertation analyzes the interrelationships among stowage planning，berthplanning and yard management，according to logistics supply chain collaborationmanagement, The framework covers work lines planning，dynamic picking containerpoint，selecting box in ship bays，etc. In this framework，mathematical models of yardmachine resources allocation rules， number matching rules，weight matching rules andRTG conflict rules were considered. By doing this，the result of auto-stow is closer to theactual business requirements.Established an intelligent stowage planning synthesis algorithms system basedon the branch and bound algorithm.This dissertation analyzes the weight of various factors affecting ship stowage，takesbranch and bound algorithm as the core，adopts business rule constraint method，Iterative algorithm, backtracking algorithm and other optimization methods，take acomprehensive calculated assessment for yard picking container points，and then selectedone to meet the optimal target from the mass solutions. This dissertation builds theevaluation system of yard picking container points，achieving the scientific plan of yardmachine operations.By means of scientific planning RTGs’ track and cranes’ work queue，thisdissertation turns out that invalid machine movement can be reduced，the collaborationwork efficiency of cranes and RTG’s can be greatly enhanced，the cost of containerterminal operations can be greatly reduced， and the efficiency and effectiveness ofterminal can be improved.This dissertation explores in-depth the key technologies of container terminalauto-stow, find new ways of system optimization in the field, proposed a new system ofresearch methods and techniques, solve the extremely complex business rules integrating problem. By applying advanced combinatorial optimization algorithm to practice, andachieved a good results.