• Solving Quadratic Assignment P...

Treffer: Solving Quadratic Assignment Problem by Using Meta-heuristic Search Method

Title:
Solving Quadratic Assignment Problem by Using Meta-heuristic Search Method
Authors:
Iraq T. Abass, Rawaa Abdulsattar, Leong WJ
Source:
Ibn Al-Haitham Journal for Pure and Applied Sciences, Vol 36, Iss 4 (2023)
Publisher Information:
College of Education for Pure Science (Ibn Al-Haitham), 2023.
Publication Year:
2023
Subject Terms:
Combinatorial optimization, Science, Guided Local Search, 0211 other engineering and technologies, Geometry, Heuristic, Metaheuristic, Firefly algorithm, 02 engineering and technology, Tabu search, 7. Clean energy, Multi-Objective Transportation Problem Optimization, Engineering, Artificial Intelligence, Computer security, FOS: Mathematics, 0202 electrical engineering, electronic engineering, information engineering, Swarm Intelligence Optimization Algorithms, Key (lock), Constraint Handling, Particle swarm optimization, Mathematical optimization, Quadratic equation, Meta heuristic, 16. Peace & justice, Computer science, Algorithm, Computational Theory and Mathematics, Quadratic assignment problem, Genetic algorithm, Control and Systems Engineering, Tabu Search, Quadratic Assignment Problems, Assignment Problems, Computer Science, Physical Sciences, Assignment problem, Weapon target assignment problem, Multiobjective Optimization in Evolutionary Algorithms, Mathematics
Document Type:
Fachzeitschrift Article<br />Other literature type
ISSN:
2521-3407
1609-4042
DOI:
10.30526/36.4.3195
DOI:
10.60692/a6cpj-6aw18
DOI:
10.60692/bbtt6-sf005
Access URL:
https://doaj.org/article/2dd7d34a393d41468a81f85a330d785e
Rights:
CC BY
Accession Number:
edsair.doi.dedup.....e80b94f1874b406f687b2540cb35ffaf
Database:
OpenAIRE

Weitere Informationen

While analytical solutions to Quadratic Assignment Problems (QAP) have indeed been since a long time, the expanding use of Evolutionary Algorithms (EAs) for similar issues gives a framework for dealing with QAP with an extraordinarily broad scope. The study's key contribution is that it normalizes all of the criteria into a single scale, regardless of their measurement systems or the requirements of minimum or maximum, relieving the researchers of the exhaustively quantifying the quality criteria. A tabu search algorithm for quadratic assignment problems (TSQAP) is proposed, which combines the limitations of tabu search with a discrete assignment problem. The effectiveness of the proposed technique has been compared to well-established alternatives, and its operating principle is illustrated with a numerical example. After repeating the solution of each issue (8) once and recording the algorithm results, it showed its agreement, once from a total (375) repetition of the experiment while the number of times the Artificial Bee Colony (ABC) arrived (2) as for the Firefly (FA) Algorithm giving (117), also Genetic (GA) and Particle Swarm (PSO) gives (120) and the Tabu Search algorithm (174). The proposed technique (TSQAP) is shown to yield a superior solution with low computing complexity. MATLAB was used to generate all of the findings (R2020b).