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