• Title/Summary/Keyword: Auto Stowage Plan

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Intelligent Decision Support System for Containership Auto-stowage Planning (컨테이너 선박의 자동 적재 계획을 위한 지능형 의사결정지원시스템)

  • Shin, J.Y.;Nam, K.C.
    • Journal of Korean Port Research
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    • v.9 no.1
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    • pp.19-32
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    • 1995
  • The objective of this paper is to suggest a decision support system allowing automated stowage planning for containerships, and provide a working prototype. Unlike most previous works in this topic which concentrated mainly on the theoretical aspects. this paper attempts to develop a feasible system for improving the speed and accuracy of stowage planning by combining practice and theoretical solution methods. The paper includes a definition of the containership stowage problem, and details on the design and development of the automated stowage plan generation routine. Several program tests are undertaken with randomly generated input data. The results suggest that the prototype system is quite meaningful even though there are still some unsolved problems. The paper concludes with a discussion of issues for future development of the decision support system.

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Decision Support System for Efficient Ship Planning of Container Terminals (효율적인 컨테이너 터미널 선적 계획을 위한 의사결정지원시스템)

  • 신재영;곽규석;남기찬
    • Journal of Korean Port Research
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    • v.13 no.2
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    • pp.255-266
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    • 1999
  • The purpose of this paper is to describe the design of the decision support system for container terminal ship planning and to introduce the implemented system. The ship planning in container terminals consists of three major decision processes -the working schedule of gantry cranes the discharging sequence of inbound containers the loading position and sequence of outbound containers. For making these decision the proposed system can provide two ship planning modes the interactive planning mode with user-friendly GUI and the automated planning made. To implement the automated planning routine we acquired the planning rules from the expert planner in container terminals and developed an expert system based on the rules. Finally we evaluated the system developed and the potential for commercialization by using container terminal data.

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