Intelligent local search strategies for solving facility layout problems with the quadratic assignment problem formulation

Chiang, Wen–Chyuan; Chiang, Chi

doi:10.1016/s0377-2217(97)00285-3

Cited by 53 publications

(29 citation statements)

References 38 publications

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“…Since the reduced QAPs in these larger cases cannot be solved to optimality within a reasonable amount of time, a heuristic method based on tabu search was applied. The data structure in our tabu search implementation is the same as that of Chiang and Chiang (1998). From Tables 1 and 2, we see that the performances of the max-max and the increasing flow methods are very close.…”

Section: Numerical Resultsmentioning

confidence: 99%

“…branch-and-bound (Salimanpur and Jafari 2008) and cutting planes (Bukard and Bonniger 1983)) are only efficient to layout problems of dimensions up to about 16 (Singh and Sharma 2006). To achieve solutions for larger cases, heuristic methods, based on the QAP, such as simulated annealing (Baykasoglu andCindy 2001, Misevicius 2003), genetic algorithms (Balakrishnan et al 2003, Lee et al 2003 and tabu search (Chiang andChiang 1998, Helm andHadley 2000) have been proposed. The performances of SA and GA have been compared by Heragu and Alfa (2003) and Tavakkoli-Moghaddain and Shanyan (1998).…”

Section: Introductionmentioning

confidence: 99%

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Integrated Facility Layout Design and Flow Assignment Problem Under Uncertainty

Zhao

Wallace

2014

INFORMS Journal on Computing

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The facility layout problem is the problem of assigning facilities to locations. We study the case of limited machine capacity, and hence multiple copies of each machine type. We take into account stochastic demand, described by several types of jobs (i.e. sequences of machine types), each with an uncertain demand level. We develop a heuristic framework allowing us to find good solutions to the stochastic case whenever it is possible to solve the corresponding deterministic Quadratic Assignment Problem, exactly or heuristically. Though the QAP is a very hard problem in its own right, our approach allows randomness (and hence relevance) to be added at only a marginal increase in computational costs.

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Section: Numerical Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Integrated Facility Layout Design and Flow Assignment Problem Under Uncertainty

Zhao

Wallace

2014

INFORMS Journal on Computing

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“…Skorin-Kapov (1990) was the first who applied a tabu search (TS) improvement type heuristic to the QAP. Chiang and Chiang (1998) applied simulated annealing, tabu search, probabilistic tabu search (PTS), a hybrid of tabu search and simulated annealing heuristics to solve the QAP. Moreover, Drezner (2008) used a memetic algorithm (MA) to solve the QAP.…”

Section: Literature Surveymentioning

confidence: 99%

A multiple criteria facility layout problem using data envelopment analysis

Bozorgi

Abedzadeh²

2011

msl

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In this paper, we propose a multi criteria decision making technique to determine an efficient solution for quadratic assignment problem. The proposed method of this paper considers transportation cost, adjacency and separation as the most important criteria to find the efficient layout. A tabu search is used to generate a set of feasible solutions and for each solution, we evaluate various criteria. The proposed model of the paper uses DEA technique to choose the most efficient units among the feasible solutions. The implementation of the proposed method is demonstrated using some benchmark problems and the results are discussed in details.

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“…Abreu et al (1999) applied the technique by trying to reduce the number of inversions associated to the problem solution, together with the cost reduction. Misevicius (2000bMisevicius ( , 2003 propose a modified simulated annealing algorithm for the QAP-M-SA-QAP and tested the algorithm on a number of instances from the library of the QAP instances (QAPLIB) and also Bos (1993a, b), Burkard and Cela (1995), Peng et al (1996), Mavridou and Pardalos (1997), Chiang and Chiang (1998), Tian et al (1996, Siu and Chang (2002), Baykasoglu (2004).…”

Section: Simulated Annealing Algorithmmentioning

confidence: 99%