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The Control Scheduling in the Container Terminal Based on Movement Traces

Author: SongWeiTao
Tutor: YeChunXiao
School: Chongqing University
Course: Applied Computer Technology
Keywords: container terminal movement traces genetic algorithm scheduling optimization
CLC: U691.3
Type: Master's thesis
Year: 2011
Downloads: 34
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Abstract

Scheduling problem is an important research topic in the control of harbor logistics operations. By increasing efficiency and reducing operating costs to improve their own competitiveness in the container terminal, has become one of the most concerns. As the core of each link in the harbor operations, mode and efficiency of control scheduling directly impact on the port’s daily business activities.The control scheduling is responsible for managing organization, resources allocation and to direct work of all containers within the container terminal business. Differences between the different ports are not considered and global businesses are not arranged in traditional researches on machinery and equipment, loading and unloading yard box and turned the three lines of local scheduling. The control scheduling in the container terminal about movement traces which are based on all the operations of the global container port, shields the inland port and harbor of the differences, to achieve the minimum container volume, at least for a consideration of the business objectives of the implementation of port operations to improve efficiency. Container terminals and port operational information system is bi-directional optimization, and ultimately both win.Firstly, the focus and the problems of current research in the control scheduling are analyzed through summarizing research in the container terminal. Second, the type and mode of operation scheduled in the container terminal are introduced, the theory of movement traces has been proposed. The container port is NP-hard problem of a situation in the control of scheduling problem. The genetic algorithm, a system for solving complex optimization problems, is recommended in the third chapter. The theory of genetic algorithms is introduced, and theory and genetic algorithm trajectory combination of nonlinear optimization method which is based on the mobile trajectory is given the encoding control scheduling, constraint handling, fitness function, the relevant operating parameters and to improve the genetic iterative operation. In the encoding, a variable-length multi-parameter cross-coding of chromosome has been proposed, making the solution trajectory model chromosome space and genetic algorithm search space correspond. Constraint handling and selection for population initialization of genetic algorithm also greatly enhanced the selection convergence performance. Finally, the genetic expression of the iterative process trajectory is expressed by the adjacency matrix of the genetic, combined with the actual container port logistics system, to prove the superiority and practicality of the method in the trajectory of the executive price, cost and the mechanical implementation of system resources.

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