首页> 外文会议>IEEE Congress on Evolutionary Computation >Evolving local search heuristics for the integrated berth allocation and quay crane assignment problem
【24h】

Evolving local search heuristics for the integrated berth allocation and quay crane assignment problem

机译:不断发展的局部搜索启发式算法,用于综合泊位分配和码头起重机分配问题

获取原文

摘要

Water Transportation is the cheapest transportation mode, which allows the transfer of very large volumes of cargo between continents. One of the most important types of ships used to transfer goods are the Container Ships, therefore, containerized trade volume is rapidly increasing. This has opened a number of challenging combinatorial optimization problems in container terminals. This paper focuses on the integrated problem Berth Allocation and Quay Crane Assignment Problem (BQ-CAP), which occur while planning incoming vessels in container terminals. We provide a Genetic Programming (GP) approach to evolve effective and robust composite dispatching rules (CDRs) to solve the problem and present a comparative study with the current state-of-art optimal approaches. The Computational results disclose the effectiveness of the presented approach.
机译:水上运输是最便宜的运输方式,它允许在各大洲之间转移非常大量的货物。用于转移货物的最重要的船舶之一是集装箱船,因此,集装箱贸易量正在迅速增加。这给集装箱码头带来了许多具有挑战性的组合优化问题。本文着重讨论泊位分配和码头起重机分配问题(BQ-CAP)的综合问题,这些问题是在计划集装箱码头的入港船只时发生的。我们提供了一种遗传规划(GP)方法来发展有效且健壮的复合调度规则(CDR)以解决该问题,并提供了与当前最先进的最佳方法的对比研究。计算结果揭示了所提出方法的有效性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号