Optimization berth allocation in container terminals: A Pyomo and Google Colab approach

Efficient berth allocation profoundly influences container terminal operations, affecting vessel waiting and turnaround times, and overall performance. This study presents a mixed-integer linear programming (MILP) model addressing the Berth Allocation Problem (BAP) in a Malaysian container port. By...

Full description

Saved in:
Bibliographic Details
Published in:Ocean & coastal management 2024-11, Vol.258, p.107359, Article 107359
Main Authors: Nazri, Siti Nur 'Ain, Mokhtar, Kasypi, Abu Bakar, Anuar, Mclellan, Benjamin Craig, Mhd Ruslan, Siti Marsila
Format: Article
Language:English
Subjects:
Berth allocation problem
Berth template
Optimization
Pyomo
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites cdi_FETCH-LOGICAL-c191t-4c21d7572498fdb87a96a41f80482be1fa8e24c687ef8aa32279e8259c8d71e33
container_end_page
container_issue
container_start_page 107359
container_title Ocean & coastal management
container_volume 258
creator Nazri, Siti Nur 'Ain
Mokhtar, Kasypi
Abu Bakar, Anuar
Mclellan, Benjamin Craig
Mhd Ruslan, Siti Marsila
description Efficient berth allocation profoundly influences container terminal operations, affecting vessel waiting and turnaround times, and overall performance. This study presents a mixed-integer linear programming (MILP) model addressing the Berth Allocation Problem (BAP) in a Malaysian container port. By incorporating the Pyomo optimization library and CBC (Coin-or Branch and Cut) solver in Google Colab, optimal berth allocations are determined, minimizing vessel turnaround times. Visualized in a Space-Time diagram, the results highlight efficient allocation strategies. Despite limitations, the study optimally resolved three instances, achieving a remarkable 38.54% reduction in overall vessel turnaround time compared to FCFS (First-Come-First-Serve) allocation. By prioritizing port turnaround time, the optimization substantially reduced berthing and departure delays, aligning with UNCTAD's call for enhanced port efficiency and accelerated decarbonization efforts.
doi_str_mv 10.1016/j.ocecoaman.2024.107359
format article
fullrecord <record><control><sourceid>elsevier_cross</sourceid><recordid>TN_cdi_crossref_primary_10_1016_j_ocecoaman_2024_107359</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0964569124003442</els_id><sourcerecordid>S0964569124003442</sourcerecordid><originalsourceid>FETCH-LOGICAL-c191t-4c21d7572498fdb87a96a41f80482be1fa8e24c687ef8aa32279e8259c8d71e33</originalsourceid><addsrcrecordid>eNqFkM9KAzEYxHNQsFafwbzA1iT7J4m3UrQKhXpQPIZvs9_alN1kyQahPr1bVrx6GhhmhuFHyB1nK854dX9cBYs2QA9-JZgoJlfmpb4gC6arIisrza_I9TgeGWOirNSCfOyH5Hr3DckFT2uM6UCh64KdDeepDT6B8xhpwtg7D934QNf09RT6QME3dBvCZ4d0EzqoKQxDDGAPN-SynZJ4-6tL8v70-LZ5znb77ctmvcss1zxlhRW8kaUUhVZtUysJuoKCt4oVStTIW1AoClspia0CyIWQGpUotVWN5JjnSyLnXRvDOEZszRBdD_FkODNnJuZo_piYMxMzM5ma67mJ070vh9GM1qG32LiINpkmuH83fgAHcnGW</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Optimization berth allocation in container terminals: A Pyomo and Google Colab approach</title><source>Elsevier</source><creator>Nazri, Siti Nur 'Ain ; Mokhtar, Kasypi ; Abu Bakar, Anuar ; Mclellan, Benjamin Craig ; Mhd Ruslan, Siti Marsila</creator><creatorcontrib>Nazri, Siti Nur 'Ain ; Mokhtar, Kasypi ; Abu Bakar, Anuar ; Mclellan, Benjamin Craig ; Mhd Ruslan, Siti Marsila</creatorcontrib><description>Efficient berth allocation profoundly influences container terminal operations, affecting vessel waiting and turnaround times, and overall performance. This study presents a mixed-integer linear programming (MILP) model addressing the Berth Allocation Problem (BAP) in a Malaysian container port. By incorporating the Pyomo optimization library and CBC (Coin-or Branch and Cut) solver in Google Colab, optimal berth allocations are determined, minimizing vessel turnaround times. Visualized in a Space-Time diagram, the results highlight efficient allocation strategies. Despite limitations, the study optimally resolved three instances, achieving a remarkable 38.54% reduction in overall vessel turnaround time compared to FCFS (First-Come-First-Serve) allocation. By prioritizing port turnaround time, the optimization substantially reduced berthing and departure delays, aligning with UNCTAD's call for enhanced port efficiency and accelerated decarbonization efforts.</description><identifier>ISSN: 0964-5691</identifier><identifier>DOI: 10.1016/j.ocecoaman.2024.107359</identifier><language>eng</language><publisher>Elsevier Ltd</publisher><subject>Berth allocation problem ; Berth template ; Optimization ; Pyomo</subject><ispartof>Ocean &amp; coastal management, 2024-11, Vol.258, p.107359, Article 107359</ispartof><rights>2024 Elsevier Ltd</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c191t-4c21d7572498fdb87a96a41f80482be1fa8e24c687ef8aa32279e8259c8d71e33</cites><orcidid>0009-0008-6910-471X ; 0000-0002-2807-0807 ; 0000-0002-4802-3864 ; 0000-0002-6050-9883</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids></links><search><creatorcontrib>Nazri, Siti Nur 'Ain</creatorcontrib><creatorcontrib>Mokhtar, Kasypi</creatorcontrib><creatorcontrib>Abu Bakar, Anuar</creatorcontrib><creatorcontrib>Mclellan, Benjamin Craig</creatorcontrib><creatorcontrib>Mhd Ruslan, Siti Marsila</creatorcontrib><title>Optimization berth allocation in container terminals: A Pyomo and Google Colab approach</title><title>Ocean &amp; coastal management</title><description>Efficient berth allocation profoundly influences container terminal operations, affecting vessel waiting and turnaround times, and overall performance. This study presents a mixed-integer linear programming (MILP) model addressing the Berth Allocation Problem (BAP) in a Malaysian container port. By incorporating the Pyomo optimization library and CBC (Coin-or Branch and Cut) solver in Google Colab, optimal berth allocations are determined, minimizing vessel turnaround times. Visualized in a Space-Time diagram, the results highlight efficient allocation strategies. Despite limitations, the study optimally resolved three instances, achieving a remarkable 38.54% reduction in overall vessel turnaround time compared to FCFS (First-Come-First-Serve) allocation. By prioritizing port turnaround time, the optimization substantially reduced berthing and departure delays, aligning with UNCTAD's call for enhanced port efficiency and accelerated decarbonization efforts.</description><subject>Berth allocation problem</subject><subject>Berth template</subject><subject>Optimization</subject><subject>Pyomo</subject><issn>0964-5691</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNqFkM9KAzEYxHNQsFafwbzA1iT7J4m3UrQKhXpQPIZvs9_alN1kyQahPr1bVrx6GhhmhuFHyB1nK854dX9cBYs2QA9-JZgoJlfmpb4gC6arIisrza_I9TgeGWOirNSCfOyH5Hr3DckFT2uM6UCh64KdDeepDT6B8xhpwtg7D934QNf09RT6QME3dBvCZ4d0EzqoKQxDDGAPN-SynZJ4-6tL8v70-LZ5znb77ctmvcss1zxlhRW8kaUUhVZtUysJuoKCt4oVStTIW1AoClspia0CyIWQGpUotVWN5JjnSyLnXRvDOEZszRBdD_FkODNnJuZo_piYMxMzM5ma67mJ070vh9GM1qG32LiINpkmuH83fgAHcnGW</recordid><startdate>20241101</startdate><enddate>20241101</enddate><creator>Nazri, Siti Nur 'Ain</creator><creator>Mokhtar, Kasypi</creator><creator>Abu Bakar, Anuar</creator><creator>Mclellan, Benjamin Craig</creator><creator>Mhd Ruslan, Siti Marsila</creator><general>Elsevier Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><orcidid>https://orcid.org/0009-0008-6910-471X</orcidid><orcidid>https://orcid.org/0000-0002-2807-0807</orcidid><orcidid>https://orcid.org/0000-0002-4802-3864</orcidid><orcidid>https://orcid.org/0000-0002-6050-9883</orcidid></search><sort><creationdate>20241101</creationdate><title>Optimization berth allocation in container terminals: A Pyomo and Google Colab approach</title><author>Nazri, Siti Nur 'Ain ; Mokhtar, Kasypi ; Abu Bakar, Anuar ; Mclellan, Benjamin Craig ; Mhd Ruslan, Siti Marsila</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c191t-4c21d7572498fdb87a96a41f80482be1fa8e24c687ef8aa32279e8259c8d71e33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Berth allocation problem</topic><topic>Berth template</topic><topic>Optimization</topic><topic>Pyomo</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Nazri, Siti Nur 'Ain</creatorcontrib><creatorcontrib>Mokhtar, Kasypi</creatorcontrib><creatorcontrib>Abu Bakar, Anuar</creatorcontrib><creatorcontrib>Mclellan, Benjamin Craig</creatorcontrib><creatorcontrib>Mhd Ruslan, Siti Marsila</creatorcontrib><collection>CrossRef</collection><jtitle>Ocean &amp; coastal management</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Nazri, Siti Nur 'Ain</au><au>Mokhtar, Kasypi</au><au>Abu Bakar, Anuar</au><au>Mclellan, Benjamin Craig</au><au>Mhd Ruslan, Siti Marsila</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Optimization berth allocation in container terminals: A Pyomo and Google Colab approach</atitle><jtitle>Ocean &amp; coastal management</jtitle><date>2024-11-01</date><risdate>2024</risdate><volume>258</volume><spage>107359</spage><pages>107359-</pages><artnum>107359</artnum><issn>0964-5691</issn><abstract>Efficient berth allocation profoundly influences container terminal operations, affecting vessel waiting and turnaround times, and overall performance. This study presents a mixed-integer linear programming (MILP) model addressing the Berth Allocation Problem (BAP) in a Malaysian container port. By incorporating the Pyomo optimization library and CBC (Coin-or Branch and Cut) solver in Google Colab, optimal berth allocations are determined, minimizing vessel turnaround times. Visualized in a Space-Time diagram, the results highlight efficient allocation strategies. Despite limitations, the study optimally resolved three instances, achieving a remarkable 38.54% reduction in overall vessel turnaround time compared to FCFS (First-Come-First-Serve) allocation. By prioritizing port turnaround time, the optimization substantially reduced berthing and departure delays, aligning with UNCTAD's call for enhanced port efficiency and accelerated decarbonization efforts.</abstract><pub>Elsevier Ltd</pub><doi>10.1016/j.ocecoaman.2024.107359</doi><orcidid>https://orcid.org/0009-0008-6910-471X</orcidid><orcidid>https://orcid.org/0000-0002-2807-0807</orcidid><orcidid>https://orcid.org/0000-0002-4802-3864</orcidid><orcidid>https://orcid.org/0000-0002-6050-9883</orcidid></addata></record>
fulltext fulltext
identifier ISSN: 0964-5691
ispartof Ocean & coastal management, 2024-11, Vol.258, p.107359, Article 107359
issn 0964-5691
language eng
recordid cdi_crossref_primary_10_1016_j_ocecoaman_2024_107359
source Elsevier
subjects Berth allocation problem
Berth template
Optimization
Pyomo
title Optimization berth allocation in container terminals: A Pyomo and Google Colab approach
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-06T15%3A04%3A11IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-elsevier_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Optimization%20berth%20allocation%20in%20container%20terminals:%20A%20Pyomo%20and%20Google%20Colab%20approach&rft.jtitle=Ocean%20&%20coastal%20management&rft.au=Nazri,%20Siti%20Nur%20'Ain&rft.date=2024-11-01&rft.volume=258&rft.spage=107359&rft.pages=107359-&rft.artnum=107359&rft.issn=0964-5691&rft_id=info:doi/10.1016/j.ocecoaman.2024.107359&rft_dat=%3Celsevier_cross%3ES0964569124003442%3C/elsevier_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c191t-4c21d7572498fdb87a96a41f80482be1fa8e24c687ef8aa32279e8259c8d71e33%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true