A survey of mat-heuristics for combinatorial optimisation problems: Variants, trends and opportunities
This survey paper presents an overview of recent application of mat-heuristics on combinatorial optimisation problems (COPs) from 2018 to 2024. In this review, we categorise the mat-heuristics into six categories based on three integration types (loose, tight and multi) and two approaches (direct...
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2024
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Online Access: | http://ir.unimas.my/id/eprint/45371/2/A%20survey%20of%20mat-heuristics%20-%20Copy.pdf http://ir.unimas.my/id/eprint/45371/ https://www.sciencedirect.com/science/article/abs/pii/S156849462400721X https://doi.org/10.1016/j.asoc.2024.111947 |
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my.unimas.ir.453712024-07-25T06:48:37Z http://ir.unimas.my/id/eprint/45371/ A survey of mat-heuristics for combinatorial optimisation problems: Variants, trends and opportunities Ngoo, Chong Man Goh, Say Leng Sze, San Nah Nasser R., Sabar Mohd Hanafi, Ahmad Hijazi Graham, Kendall QA Mathematics QA76 Computer software This survey paper presents an overview of recent application of mat-heuristics on combinatorial optimisation problems (COPs) from 2018 to 2024. In this review, we categorise the mat-heuristics into six categories based on three integration types (loose, tight and multi) and two approaches (direct and decomposition). Descriptive statistics reveal that tight integration mat-heuristics are widely favoured. It is also observed that direct approaches are more commonly employed compared to decomposition approaches, perhaps due to the complexity involved in the latter. Next, we briefly present the mechanism of each mat-heuristic and its performance in a comparison to other state-of-the-art solution methodologies. CPLEX emerges as the predominant solver. Mat-heuristics have demonstrated their versatility across COPs, consistently achieving or setting new best-known solutions (BKS). We analyse highly effective mat-heuristics and outline the implementation strategies employed by those that managed to set new BKS. In addition, we discuss the advantages and challenges of utilising mat-heuristics as a solution methodology, as well as future research opportunities in this domain. Elsevier B.V. 2024 Article PeerReviewed text en http://ir.unimas.my/id/eprint/45371/2/A%20survey%20of%20mat-heuristics%20-%20Copy.pdf Ngoo, Chong Man and Goh, Say Leng and Sze, San Nah and Nasser R., Sabar and Mohd Hanafi, Ahmad Hijazi and Graham, Kendall (2024) A survey of mat-heuristics for combinatorial optimisation problems: Variants, trends and opportunities. Applied Soft Computing, 164. pp. 1-17. ISSN 1872-9681 https://www.sciencedirect.com/science/article/abs/pii/S156849462400721X https://doi.org/10.1016/j.asoc.2024.111947 |
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QA Mathematics QA76 Computer software Ngoo, Chong Man Goh, Say Leng Sze, San Nah Nasser R., Sabar Mohd Hanafi, Ahmad Hijazi Graham, Kendall A survey of mat-heuristics for combinatorial optimisation problems: Variants, trends and opportunities |
description |
This survey paper presents an overview of recent application of mat-heuristics on combinatorial optimisation
problems (COPs) from 2018 to 2024. In this review, we categorise the mat-heuristics into six categories
based on three integration types (loose, tight and multi) and two approaches (direct and decomposition).
Descriptive statistics reveal that tight integration mat-heuristics are widely favoured. It is also observed that
direct approaches are more commonly employed compared to decomposition approaches, perhaps due to
the complexity involved in the latter. Next, we briefly present the mechanism of each mat-heuristic and
its performance in a comparison to other state-of-the-art solution methodologies. CPLEX emerges as the
predominant solver. Mat-heuristics have demonstrated their versatility across COPs, consistently achieving
or setting new best-known solutions (BKS). We analyse highly effective mat-heuristics and outline the
implementation strategies employed by those that managed to set new BKS. In addition, we discuss the
advantages and challenges of utilising mat-heuristics as a solution methodology, as well as future research
opportunities in this domain. |
format |
Article |
author |
Ngoo, Chong Man Goh, Say Leng Sze, San Nah Nasser R., Sabar Mohd Hanafi, Ahmad Hijazi Graham, Kendall |
author_facet |
Ngoo, Chong Man Goh, Say Leng Sze, San Nah Nasser R., Sabar Mohd Hanafi, Ahmad Hijazi Graham, Kendall |
author_sort |
Ngoo, Chong Man |
title |
A survey of mat-heuristics for combinatorial optimisation problems: Variants, trends and opportunities |
title_short |
A survey of mat-heuristics for combinatorial optimisation problems: Variants, trends and opportunities |
title_full |
A survey of mat-heuristics for combinatorial optimisation problems: Variants, trends and opportunities |
title_fullStr |
A survey of mat-heuristics for combinatorial optimisation problems: Variants, trends and opportunities |
title_full_unstemmed |
A survey of mat-heuristics for combinatorial optimisation problems: Variants, trends and opportunities |
title_sort |
survey of mat-heuristics for combinatorial optimisation problems: variants, trends and opportunities |
publisher |
Elsevier B.V. |
publishDate |
2024 |
url |
http://ir.unimas.my/id/eprint/45371/2/A%20survey%20of%20mat-heuristics%20-%20Copy.pdf http://ir.unimas.my/id/eprint/45371/ https://www.sciencedirect.com/science/article/abs/pii/S156849462400721X https://doi.org/10.1016/j.asoc.2024.111947 |
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13.18916 |