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Multi-Objectives Memetic Discrete Differential Evolution Algorithm for Solving the Container Pre-Marshalling Problem

The Container Pre-marshalling Problem (CPMP) has the significant effect of reducing ship berthing time and can help in increasing terminal turnover rate. In order to solve the CPMP, this research proposes a Multi-objectives Memetic Discrete Differential Evolution algorithm (MODDE). To date, existing...

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Main Authors: Mustafa, Hossam M. J., Ayob, Masri, Ahmad Nazri, Mohd Zakree, Abu-Taleb, Sawsan
Format: Article
Language:English
Published: Universiti Utara Malaysia Press 2019
Subjects:
Q Science (General)
Online Access:https://repo.uum.edu.my/id/eprint/29114/1/JICT%2018%2001%202019%2077-96.pdf
https://repo.uum.edu.my/id/eprint/29114/
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spelling my.uum.repo.291142023-01-29T01:22:10Z https://repo.uum.edu.my/id/eprint/29114/ Multi-Objectives Memetic Discrete Differential Evolution Algorithm for Solving the Container Pre-Marshalling Problem Mustafa, Hossam M. J. Ayob, Masri Ahmad Nazri, Mohd Zakree Abu-Taleb, Sawsan Q Science (General) The Container Pre-marshalling Problem (CPMP) has the significant effect of reducing ship berthing time and can help in increasing terminal turnover rate. In order to solve the CPMP, this research proposes a Multi-objectives Memetic Discrete Differential Evolution algorithm (MODDE). To date, existing research in CPMP only focuses on single-objective approaches. However, this is not a suitable approach due to the considerable effort required to validate the hard constraints of CPMP. Therefore, this work aims at addressing the effect of minimizing the number of miss-overlaid containers on the total number of movements in building the final feasible bay layout by embedding it in the multi-objectives evaluation function. The proposed algorithm combines the Discrete Differential Evolution mutation with the Memetic Algorithm evolutionary steps in order to find high quality CPMP solutions, achieve high convergence rate and avoid premature convergence and local optima problems. In addition, it improves the exploration and exploitation capabilities of the algorithm. The standard pre-marshalling benchmark dataset (i.e., Bortfeldt-Forster) is used to evaluate the effectiveness of the proposed algorithm. The experimental results reveal that the proposed MODDE algorithm can find good solutions on instances of the standard pre-marshalling benchmarks. This demonstrates that using the multi-objectives approach with a combination of the Discrete Differential Evolution mutation and the Memetic Algorithm evolutionary is a suitable approach for solving multi-objectives CPMP. Universiti Utara Malaysia Press 2019 Article PeerReviewed application/pdf en https://repo.uum.edu.my/id/eprint/29114/1/JICT%2018%2001%202019%2077-96.pdf Mustafa, Hossam M. J. and Ayob, Masri and Ahmad Nazri, Mohd Zakree and Abu-Taleb, Sawsan (2019) Multi-Objectives Memetic Discrete Differential Evolution Algorithm for Solving the Container Pre-Marshalling Problem. Journal of Information and Communication Technology, 18 (1). pp. 77-96. ISSN 2180-3862
institution Universiti Utara Malaysia
building UUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Utara Malaysia
content_source UUM Institutional Repository
url_provider http://repo.uum.edu.my/
language English
topic Q Science (General)
spellingShingle Q Science (General)
Mustafa, Hossam M. J.
Ayob, Masri
Ahmad Nazri, Mohd Zakree
Abu-Taleb, Sawsan
Multi-Objectives Memetic Discrete Differential Evolution Algorithm for Solving the Container Pre-Marshalling Problem
description The Container Pre-marshalling Problem (CPMP) has the significant effect of reducing ship berthing time and can help in increasing terminal turnover rate. In order to solve the CPMP, this research proposes a Multi-objectives Memetic Discrete Differential Evolution algorithm (MODDE). To date, existing research in CPMP only focuses on single-objective approaches. However, this is not a suitable approach due to the considerable effort required to validate the hard constraints of CPMP. Therefore, this work aims at addressing the effect of minimizing the number of miss-overlaid containers on the total number of movements in building the final feasible bay layout by embedding it in the multi-objectives evaluation function. The proposed algorithm combines the Discrete Differential Evolution mutation with the Memetic Algorithm evolutionary steps in order to find high quality CPMP solutions, achieve high convergence rate and avoid premature convergence and local optima problems. In addition, it improves the exploration and exploitation capabilities of the algorithm. The standard pre-marshalling benchmark dataset (i.e., Bortfeldt-Forster) is used to evaluate the effectiveness of the proposed algorithm. The experimental results reveal that the proposed MODDE algorithm can find good solutions on instances of the standard pre-marshalling benchmarks. This demonstrates that using the multi-objectives approach with a combination of the Discrete Differential Evolution mutation and the Memetic Algorithm evolutionary is a suitable approach for solving multi-objectives CPMP.
format Article
author Mustafa, Hossam M. J.
Ayob, Masri
Ahmad Nazri, Mohd Zakree
Abu-Taleb, Sawsan
author_facet Mustafa, Hossam M. J.
Ayob, Masri
Ahmad Nazri, Mohd Zakree
Abu-Taleb, Sawsan
author_sort Mustafa, Hossam M. J.
title Multi-Objectives Memetic Discrete Differential Evolution Algorithm for Solving the Container Pre-Marshalling Problem
title_short Multi-Objectives Memetic Discrete Differential Evolution Algorithm for Solving the Container Pre-Marshalling Problem
title_full Multi-Objectives Memetic Discrete Differential Evolution Algorithm for Solving the Container Pre-Marshalling Problem
title_fullStr Multi-Objectives Memetic Discrete Differential Evolution Algorithm for Solving the Container Pre-Marshalling Problem
title_full_unstemmed Multi-Objectives Memetic Discrete Differential Evolution Algorithm for Solving the Container Pre-Marshalling Problem
title_sort multi-objectives memetic discrete differential evolution algorithm for solving the container pre-marshalling problem
publisher Universiti Utara Malaysia Press
publishDate 2019
url https://repo.uum.edu.my/id/eprint/29114/1/JICT%2018%2001%202019%2077-96.pdf
https://repo.uum.edu.my/id/eprint/29114/
_version_ 1756687048084815872
score 13.211869

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