Review On The Methods To Solve Combinatorial Optimization Problems Particularly:Quadratic Assignment Model

Mohd Aboobaider, Burhanuddin and Hameed, Asaad Shakir and Ngo, Hea Choon and Mutar, Modhi Lafta and Bilal, Wassim Habib (2018) Review On The Methods To Solve Combinatorial Optimization Problems Particularly:Quadratic Assignment Model. International Journal Of Engineering & Technology, 7. pp. 15-20. ISSN 2319-8613

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The quadratic assignment problem (QAP) is one of the fundamental combinatorial optimization problem (COPs) in the branch of optimization or operation research in mathematics,from the category of the Facilities Location Problems (FLPs).The quadratic assignment problem (QAP) be appropriate to the group of NP-hard issues and is measured as a challenging problem of the combinatorial optimization.QAP in Location Theory considers one of the problems of facilities tracing which the rate of locating a facility be determined by the spaces between facilities as well as the communication among the further facilities.QAP was presented in 1957 by Beckman and Koopmans as they were attempting to model a problem of facilities location.To survey the researcher’s works for QAP and applied,the mapped research landscape outlines literature into a logical classification and discovers this field basic characteristics represented on the motivation to use the quadratic assignment problem applied in hospital layout and campus planning.This survey achieved a concentrated each QAP article search in three key databases:Web of Science,Science Direct,and IEEE Xplore.Those databases are regarded extensive adequate in covering QAP and the methods utilized in solving QAP.

Item Type: Article
Uncontrolled Keywords: Quadratic Assignment Problem, Metaheuristic Algorithms, Combinatorial Optimization Problems.
Subjects: Q Science > Q Science (General)
Q Science > QA Mathematics
Divisions: Faculty of Information and Communication Technology
Depositing User: Mohd. Nazir Taib
Date Deposited: 12 Jun 2019 07:30
Last Modified: 18 Aug 2021 23:52
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