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

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Abstract

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 (BQCAP), which occur while planning incoming vessels in container terminals. We provide a Genetic Programming (GP) approach for evolving 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.
Original languageEnglish
Title of host publicationProceedings of the 2016 IEEE World Congress on Evolutionary Computation
PublisherIEEE
Number of pages8
ISBN (Electronic)978-1-5090-0623-6, 978-1-5090-0622-9
ISBN (Print)978-1-5090-0624-3
DOIs
Publication statusPublished - 21 Nov 2016
Event2016 IEEE World Congress on Computational Intelligence - Vancouver, Canada
Duration: 25 Jul 201629 Jul 2016

Conference

Conference2016 IEEE World Congress on Computational Intelligence
Abbreviated titleIEEE WCCI
CountryCanada
CityVancouver
Period25/07/1629/07/16

Keywords

  • containers
  • cranes
  • marine vehicles
  • resources management
  • ports (computers)
  • mathematical model
  • layout

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