Solving the quadratic assignment problem by a Hybrid Algorithm

Solving the quadratic assignment problem by a Hybrid Algorithm

This paper presents a hybrid algorithm to solve the Quadratic Assignment Problem (QAP). The proposed algorithminvolves using the Greedy Randomized Adaptive Search Procedure (GRASP) to obtain an initial solution, and then using a combinedSimulated Annealing (SA) and Tabu Search (TS) algorithm to impr...

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Main Authors: GUNAWAN, Aldy, NG, Kien Ming, POH, Kim Leng
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2011
Subjects:
Quadratic Assignment Problem
Hybrid Algorithm
GRASP
Simulated Annealing
Tabu Search
Programming Languages and Compilers
Software Engineering
Online Access:https://ink.library.smu.edu.sg/sis_research/4028
https://ink.library.smu.edu.sg/context/sis_research/article/5030/viewcontent/ISC_Paper_Template_in_A4__V1_.pdf
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Institution: Singapore Management University
Language: English
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spelling sg-smu-ink.sis_research-50302018-05-28T03:53:58Z Solving the quadratic assignment problem by a Hybrid Algorithm GUNAWAN, Aldy NG, Kien Ming POH, Kim Leng This paper presents a hybrid algorithm to solve the Quadratic Assignment Problem (QAP). The proposed algorithminvolves using the Greedy Randomized Adaptive Search Procedure (GRASP) to obtain an initial solution, and then using a combinedSimulated Annealing (SA) and Tabu Search (TS) algorithm to improve the solution. Experimental results indicate that the hybridalgorithm is able to obtain good quality solutions for QAPLIB test problems within reasonable computation time. 2011-01-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/4028 info:doi/10.18517/ijaseit.1.1.10 https://ink.library.smu.edu.sg/context/sis_research/article/5030/viewcontent/ISC_Paper_Template_in_A4__V1_.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Quadratic Assignment Problem Hybrid Algorithm GRASP Simulated Annealing Tabu Search Programming Languages and Compilers Software Engineering
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Quadratic Assignment Problem
Hybrid Algorithm
GRASP
Simulated Annealing
Tabu Search
Programming Languages and Compilers
Software Engineering
spellingShingle Quadratic Assignment Problem
Hybrid Algorithm
GRASP
Simulated Annealing
Tabu Search
Programming Languages and Compilers
Software Engineering
GUNAWAN, Aldy
NG, Kien Ming
POH, Kim Leng
Solving the quadratic assignment problem by a Hybrid Algorithm
description This paper presents a hybrid algorithm to solve the Quadratic Assignment Problem (QAP). The proposed algorithminvolves using the Greedy Randomized Adaptive Search Procedure (GRASP) to obtain an initial solution, and then using a combinedSimulated Annealing (SA) and Tabu Search (TS) algorithm to improve the solution. Experimental results indicate that the hybridalgorithm is able to obtain good quality solutions for QAPLIB test problems within reasonable computation time.
format text
author GUNAWAN, Aldy
NG, Kien Ming
POH, Kim Leng
author_facet GUNAWAN, Aldy
NG, Kien Ming
POH, Kim Leng
author_sort GUNAWAN, Aldy
title Solving the quadratic assignment problem by a Hybrid Algorithm
title_short Solving the quadratic assignment problem by a Hybrid Algorithm
title_full Solving the quadratic assignment problem by a Hybrid Algorithm
title_fullStr Solving the quadratic assignment problem by a Hybrid Algorithm
title_full_unstemmed Solving the quadratic assignment problem by a Hybrid Algorithm
title_sort solving the quadratic assignment problem by a hybrid algorithm
publisher Institutional Knowledge at Singapore Management University
publishDate 2011
url https://ink.library.smu.edu.sg/sis_research/4028
https://ink.library.smu.edu.sg/context/sis_research/article/5030/viewcontent/ISC_Paper_Template_in_A4__V1_.pdf
_version_ 1770574119458308096

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