Biased random key genetic algorithm for the Tactical Berth Allocation Problem

Eduardo Lalla-Ruiz, José Luis González-Velarde, Belén Melián-Batista, J. Marcos Moreno-Vega

    Research output: Contribution to journalArticleAcademicpeer-review

    49 Citations (Scopus)

    Abstract

    The Tactical Berth Allocation Problem (TBAP) aims to allocate incoming ships to berthing positions and assign quay crane profiles to them (i.e. number of quay cranes per time step). The goals of the TBAP are both the minimization of the housekeeping costs derived from the transshipment container flows between ships, and the maximization of the total value of the quay crane profiles assigned to the ships. In order to obtain good quality solutions with considerably short computational effort, this paper proposes a biased random key genetic algorithm for solving this problem. The computational experiments and the comparison with other solutions approaches presented in the related literature for tackling the TBAP show that the proposed algorithm is applicable to efficiently solve this difficult and essential container terminal problem. The problem instances used in this paper are composed of both, those reported in the literature and a new benchmark suite proposed in this work for taking into consideration other realistic scenarios.
    Original languageEnglish
    Pages (from-to)60-76
    JournalApplied Soft Computing
    Volume22
    DOIs
    Publication statusPublished - 1 Sep 2014

    Keywords

    • Maritime Logistics
    • Optimization
    • Metaheuristics
    • Genetic Algorithm

    Fingerprint

    Dive into the research topics of 'Biased random key genetic algorithm for the Tactical Berth Allocation Problem'. Together they form a unique fingerprint.

    Cite this