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

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@InProceedings{El-boghdadly:2016:CEC,
  author =       "Tamer El-boghdadly and Mohamed Bader-El-Den and 
                 Dylan Jones",
  title =        "Evolving local search heuristics for the integrated
                 berth allocation and quay crane assignment problem",
  booktitle =    "Proceedings of 2016 IEEE Congress on Evolutionary
                 Computation (CEC 2016)",
  year =         "2016",
  editor =       "Yew-Soon Ong",
  pages =        "2880--2887",
  address =      "Vancouver",
  month =        "24-29 " # jul,
  publisher =    "IEEE Press",
  keywords =     "genetic algorithms, genetic programming, Berth
                 Allocation, Quay Crane Assignment, Container Terminal
                 Operations, Composite dispatching rules, Optimization;
                 Scheduling",
  isbn13 =       "978-1-5090-0623-6",
  DOI =          "doi:10.1109/CEC.2016.7744153",
  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 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.",
  notes =        "WCCI2016",
}

Genetic Programming entries for Tamer El-boghdadly Mohamed Bahy Bader-El-Den Dylan Jones

Citations