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Minimizing the Total Service Time of Discrete Dynamic Berth Allocation Problem by an Iterated Greedy Heuristic

Berth allocation is the forefront operation performed when ships arrive at a port and is a critical task in container port optimization. Minimizing the time ships spend at berths constitutes an important objective of berth allocation problems. This study focuses on the discrete dynamic berth allocat...

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Detalles Bibliográficos
Autores principales: Lin, Shih-Wei, Ying, Kuo-Ching, Wan, Shu-Yen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4175388/
https://www.ncbi.nlm.nih.gov/pubmed/25295295
http://dx.doi.org/10.1155/2014/218925
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author Lin, Shih-Wei
Ying, Kuo-Ching
Wan, Shu-Yen
author_facet Lin, Shih-Wei
Ying, Kuo-Ching
Wan, Shu-Yen
author_sort Lin, Shih-Wei
collection PubMed
description Berth allocation is the forefront operation performed when ships arrive at a port and is a critical task in container port optimization. Minimizing the time ships spend at berths constitutes an important objective of berth allocation problems. This study focuses on the discrete dynamic berth allocation problem (discrete DBAP), which aims to minimize total service time, and proposes an iterated greedy (IG) algorithm to solve it. The proposed IG algorithm is tested on three benchmark problem sets. Experimental results show that the proposed IG algorithm can obtain optimal solutions for all test instances of the first and second problem sets and outperforms the best-known solutions for 35 out of 90 test instances of the third problem set.
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spelling pubmed-41753882014-10-07 Minimizing the Total Service Time of Discrete Dynamic Berth Allocation Problem by an Iterated Greedy Heuristic Lin, Shih-Wei Ying, Kuo-Ching Wan, Shu-Yen ScientificWorldJournal Research Article Berth allocation is the forefront operation performed when ships arrive at a port and is a critical task in container port optimization. Minimizing the time ships spend at berths constitutes an important objective of berth allocation problems. This study focuses on the discrete dynamic berth allocation problem (discrete DBAP), which aims to minimize total service time, and proposes an iterated greedy (IG) algorithm to solve it. The proposed IG algorithm is tested on three benchmark problem sets. Experimental results show that the proposed IG algorithm can obtain optimal solutions for all test instances of the first and second problem sets and outperforms the best-known solutions for 35 out of 90 test instances of the third problem set. Hindawi Publishing Corporation 2014 2014-09-08 /pmc/articles/PMC4175388/ /pubmed/25295295 http://dx.doi.org/10.1155/2014/218925 Text en Copyright © 2014 Shih-Wei Lin et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Lin, Shih-Wei
Ying, Kuo-Ching
Wan, Shu-Yen
Minimizing the Total Service Time of Discrete Dynamic Berth Allocation Problem by an Iterated Greedy Heuristic
title Minimizing the Total Service Time of Discrete Dynamic Berth Allocation Problem by an Iterated Greedy Heuristic
title_full Minimizing the Total Service Time of Discrete Dynamic Berth Allocation Problem by an Iterated Greedy Heuristic
title_fullStr Minimizing the Total Service Time of Discrete Dynamic Berth Allocation Problem by an Iterated Greedy Heuristic
title_full_unstemmed Minimizing the Total Service Time of Discrete Dynamic Berth Allocation Problem by an Iterated Greedy Heuristic
title_short Minimizing the Total Service Time of Discrete Dynamic Berth Allocation Problem by an Iterated Greedy Heuristic
title_sort minimizing the total service time of discrete dynamic berth allocation problem by an iterated greedy heuristic
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4175388/
https://www.ncbi.nlm.nih.gov/pubmed/25295295
http://dx.doi.org/10.1155/2014/218925
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