Kheiri, Ahmed ![]() |
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Abstract
A square matrix of distinct numbers in which every row, column and both diagonals have the same total is referred to as a magic square. Constructing a magic square of a given order is considered a difficult computational problem, particularly when additional constraints are imposed. Hyper-heuristics are emerging high-level search methodologies that explore the space of heuristics for solving a given problem. In this study, we present a range of effective selection hyper-heuristics mixing perturbative low-level heuristics for constructing the constrained version of magic squares. The results show that selection hyper-heuristics, even the non-learning ones deliver an outstanding performance, beating the best-known heuristic solution on average.
Item Type: | Article |
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Date Type: | Publication |
Status: | Published |
Schools: | Computer Science & Informatics |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Publisher: | Oxford University Press |
ISSN: | 0010-4620 |
Date of First Compliant Deposit: | 23 June 2016 |
Last Modified: | 20 Nov 2024 13:30 |
URI: | https://orca.cardiff.ac.uk/id/eprint/85915 |
Citation Data
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