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컨테이너의 최적 적하계획을 위한 PPGA

PPGA for the Optimal Load Planning of Containers

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참고문헌

키워드

주제분류해상운송학

초록

컨테이너 적하계획은 항만 장비운용의 효율성을 결정짓는 주요 요인 중 하나이다. 적하계획 문제에 유전알고리즘을 응용할 때 처리작업 수가 많게 되면, 기존의 방법으로 많은 시간이 걸린다. 이 문제를 해결하기 위하여 본 논문에서는 이주모델과 링구조 기반의 의사병렬 유전알고리즘을 개발하고 컨테이너의 최적 적하순서를 결정하는 문제에 적용하여 그 유효성을 밝힌다.

Abstract

The container load planning is one of key factors for efficient operations of handling equipments at container ports. When the number of containers are large, finding a good solution using the conventional genetic algorithm is very time consuming. To obtain a good solution with considerably small effort, in this paper a pseudo-parallel genetic algorithm(PPGA) based on both the migration model and the ring topology is developed. The performance of the PPGA is demonstrated through a test problem of determining the optimal loading sequence of the containers.

참고문헌 (12)

  1. "유전알고리즘과 그 응용" (2000), 교우사.
  2. "The berth allocation problem heuristic method using genetic algorithm", pp.109~114 (1996)
  3. "Parallel Genetic Algorithms,Parallel & Distributed Computing Handbook" (1996), McGraw-Hill.
  4. "Development of a methodology for containership load planning" (1982)
  5. "An analysis of the behavior of a class of genetic adaptive systems The University of Michigan" (1975)
  6. "Containership load planning heuristic for a transtainer based container port" (1981)
  7. "Optimization of control parameters for genetic algorithms", smc-16(1), pp.122~128 (1986)
  8. "Load scheduling using a genetic algorithm in port container terminals", 23(4), pp.546~660 (1997)
  9. "Mathematical models and search techniques for containership load planning" (1998)
  10. "Genetic algorithm to schedule container transfers at multimodal terminals", 6, pp.311~329 (1999)
  11. "Berth allocation planning in the public berth system by genetic algorithms", 131, pp.282~292 (2001)
  12. "A branch-and-bound solution method for the crane scheduling problem", 24b, pp.159~172 (1990)

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