Ant colony optimization for solving university facility layout problem
Quadratic Assignment Problems (QAP) is classified as the NP hard problem. It has been used to model a lot of problem in several areas such as operational research, combinatorial data analysis and also parallel and distributed computing, optimization problem such as graph portioning and Travel Salesm...
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my.utm.509022017-09-14T07:59:12Z http://eprints.utm.my/id/eprint/50902/ Ant colony optimization for solving university facility layout problem Mohd. Jani, Nurul Hafiza Mohd. Radzi, Nor Haizan Ngadiman, Mohd. Salihin QA75 Electronic computers. Computer science Quadratic Assignment Problems (QAP) is classified as the NP hard problem. It has been used to model a lot of problem in several areas such as operational research, combinatorial data analysis and also parallel and distributed computing, optimization problem such as graph portioning and Travel Salesman Problem (TSP). In the literature, researcher use exact algorithm, heuristics algorithm and metaheuristic approaches to solve QAP problem. QAP is largely applied in facility layout problem (FLP). In this paper we used QAP to model university facility layout problem. There are 8 facilities that need to be assigned to 8 locations. Hence we have modeled a QAP problem with n ≤ 10 and developed an Ant Colony Optimization (ACO) algorithm to solve the university facility layout problem. The objective is to assign n facilities to n locations such that the minimum product of flows and distances is obtained. Flow is the movement from one to another facility, whereas distance is the distance between one locations of a facility to other facilities locations. The objective of the QAP is to obtain minimum total walking (flow) of lecturers from one destination to another (distance). 2013 Conference or Workshop Item PeerReviewed Mohd. Jani, Nurul Hafiza and Mohd. Radzi, Nor Haizan and Ngadiman, Mohd. Salihin (2013) Ant colony optimization for solving university facility layout problem. In: Proceedings Of The 20th National Symposium On Mathematical Sciences (SKSM20): Research In Mathematical Sciences: A Catalyst For Creativity And Innovation, PTS A And B. http://dx.doi.org/10.1063/1.4801286 |
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QA75 Electronic computers. Computer science Mohd. Jani, Nurul Hafiza Mohd. Radzi, Nor Haizan Ngadiman, Mohd. Salihin Ant colony optimization for solving university facility layout problem |
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Quadratic Assignment Problems (QAP) is classified as the NP hard problem. It has been used to model a lot of problem in several areas such as operational research, combinatorial data analysis and also parallel and distributed computing, optimization problem such as graph portioning and Travel Salesman Problem (TSP). In the literature, researcher use exact algorithm, heuristics algorithm and metaheuristic approaches to solve QAP problem. QAP is largely applied in facility layout problem (FLP). In this paper we used QAP to model university facility layout problem. There are 8 facilities that need to be assigned to 8 locations. Hence we have modeled a QAP problem with n ≤ 10 and developed an Ant Colony Optimization (ACO) algorithm to solve the university facility layout problem. The objective is to assign n facilities to n locations such that the minimum product of flows and distances is obtained. Flow is the movement from one to another facility, whereas distance is the distance between one locations of a facility to other facilities locations. The objective of the QAP is to obtain minimum total walking (flow) of lecturers from one destination to another (distance). |
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Conference or Workshop Item |
author |
Mohd. Jani, Nurul Hafiza Mohd. Radzi, Nor Haizan Ngadiman, Mohd. Salihin |
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Mohd. Jani, Nurul Hafiza Mohd. Radzi, Nor Haizan Ngadiman, Mohd. Salihin |
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Mohd. Jani, Nurul Hafiza |
title |
Ant colony optimization for solving university facility layout problem |
title_short |
Ant colony optimization for solving university facility layout problem |
title_full |
Ant colony optimization for solving university facility layout problem |
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Ant colony optimization for solving university facility layout problem |
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Ant colony optimization for solving university facility layout problem |
title_sort |
ant colony optimization for solving university facility layout problem |
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2013 |
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http://eprints.utm.my/id/eprint/50902/ http://dx.doi.org/10.1063/1.4801286 |
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