基于作业资源优化调配的集装箱码头智能配载关键技术研究
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摘要
集装箱码头智能配载是一项信息技术和集装箱码头操作管理技术相结合的研究课题。配载作为集装箱码头物流供应链核心环节，对集装箱码头装卸工艺流程管理起到关键作用，但是，国内外尚没有有效的方法和应用，来解决这个复杂多约束的难题。
随着航运业的发展和集装箱船的日趋大型化，传统的人工配载方式需要考虑的因素越来越多，依靠人工经验来科学调配桥吊、拖车、轮胎吊等码头作业资源，实现高效、准确地配载也越来越困难。因此，寻找一种合理有效的智能优化途径，来解决此类多目标组合优化问题，既能满足工程时效性要求，又能实现对生产作业的优化管理，是对科研人员的一种挑战。
本文在多年大型现代化集装箱码头操作管理系统的研究开发基础上，立足于工程实践中遇到的新的难点技术问题，目的是实现配载的智能化、自动化，将配载员从繁重的配载脑力劳动工作中解放出来。
本文主要研究内容是以泊位计划、船舶计划、堆场计划、设备控制等为依托，通过研究集装箱码头业务管理中作业资源的动态调配，分析配载、堆场管理等环节的相互作用关系，建立集装箱码头作业资源关键指标评价体系，构建智能配载三层规划数学模型和综合算法体系，实现了船舶配载的快速、准确、高效、智能，使配载水平和作业效率得到巨大提升。
主要创新点如下：
1、构建了以作业资源动态调配的集装箱码头智能配载三层规划模型。
本文从物流供应链协同管理角度，分析配载和泊位计划、堆场管理等环节的相互作用关系，提炼业务规则和建立业务模型，提出了作业路规划、动态取箱点、贝位派箱的智能配载三层规划框架。对堆场机械资源分配规则、数量匹配规则、重量匹配规则和RTG冲突规则等建立不同的数学模型，从而使配载方案更加贴近实际的配载业务要求。
2、建立了以分支限界算法为核心的智能配载综合算法体系。
通过分析影响船舶配载各个因素的权重，以分支限界算法为核心，采用业务规则约束法、迭代算法、回溯算法等多种优化手段，对堆场取箱点等关键环节进行综合计算评估，从海量系统解中快速选取满足优化目标的解。构建堆场取箱点选取的评估体系，实现堆场机械作业的科学规划。通过科学规划机械走位和桥吊作业顺序，减少了无效机械移动，促进了码头桥吊、轮胎吊的协同作业效率，减少了集装箱码头的作业成本，提高码头运营效率和效益。
本文对集装箱码头智能化配载关键技术进行了深入探索，找到了该领域系统优化的新途径，提出了新的研究方法和技术体系，解决了集装箱码头智能化配载极其复杂的业务规则集成优化问题，把先进的优化算法应用到实践中，并取得了很好的应用成果。
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.
随着航运业的发展和集装箱船的日趋大型化，传统的人工配载方式需要考虑的因素越来越多，依靠人工经验来科学调配桥吊、拖车、轮胎吊等码头作业资源，实现高效、准确地配载也越来越困难。因此，寻找一种合理有效的智能优化途径，来解决此类多目标组合优化问题，既能满足工程时效性要求，又能实现对生产作业的优化管理，是对科研人员的一种挑战。
本文在多年大型现代化集装箱码头操作管理系统的研究开发基础上，立足于工程实践中遇到的新的难点技术问题，目的是实现配载的智能化、自动化，将配载员从繁重的配载脑力劳动工作中解放出来。
本文主要研究内容是以泊位计划、船舶计划、堆场计划、设备控制等为依托，通过研究集装箱码头业务管理中作业资源的动态调配，分析配载、堆场管理等环节的相互作用关系，建立集装箱码头作业资源关键指标评价体系，构建智能配载三层规划数学模型和综合算法体系，实现了船舶配载的快速、准确、高效、智能，使配载水平和作业效率得到巨大提升。
主要创新点如下：
1、构建了以作业资源动态调配的集装箱码头智能配载三层规划模型。
本文从物流供应链协同管理角度，分析配载和泊位计划、堆场管理等环节的相互作用关系，提炼业务规则和建立业务模型，提出了作业路规划、动态取箱点、贝位派箱的智能配载三层规划框架。对堆场机械资源分配规则、数量匹配规则、重量匹配规则和RTG冲突规则等建立不同的数学模型，从而使配载方案更加贴近实际的配载业务要求。
2、建立了以分支限界算法为核心的智能配载综合算法体系。
通过分析影响船舶配载各个因素的权重，以分支限界算法为核心，采用业务规则约束法、迭代算法、回溯算法等多种优化手段，对堆场取箱点等关键环节进行综合计算评估，从海量系统解中快速选取满足优化目标的解。构建堆场取箱点选取的评估体系，实现堆场机械作业的科学规划。通过科学规划机械走位和桥吊作业顺序，减少了无效机械移动，促进了码头桥吊、轮胎吊的协同作业效率，减少了集装箱码头的作业成本，提高码头运营效率和效益。
本文对集装箱码头智能化配载关键技术进行了深入探索，找到了该领域系统优化的新途径，提出了新的研究方法和技术体系，解决了集装箱码头智能化配载极其复杂的业务规则集成优化问题，把先进的优化算法应用到实践中，并取得了很好的应用成果。
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.
引文
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