Solving quadratic assignment problems by differential evolution

Kushida, Jun-ichi; Oba, Kazuhisa; Hara, Akira; Takahama, Tetsuyuki

doi:10.1109/scis-isis.2012.6505170

Cited by 7 publications

(13 citation statements)

References 9 publications

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“…However, the DDE algorithm operation is more successful and efficient when the local search is used. In a study earlier conducted by Kushida et al (2012) the DE was modified to a discrete optimization problem and afterward used in solving the QAP. Similarly, the use of insertion and swap was employed by Tasgetiren et al (2013) in modifying DDE with the local search-based modification.…”

Section: Literature Reviewmentioning

confidence: 99%

A new hybrid approach based on discrete differential evolution algorithm to enhancement solutions of quadratic assignment problem

Hameed¹,

Aboobaider²,

Mutar³

et al. 2020

10.5267/j.ijiec

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The Combinatorial Optimization Problem (COPs) is one of the branches of applied mathematics and computer sciences, which is accompanied by many problems such as Facility Layout Problem (FLP), Vehicle Routing Problem (VRP), etc. Even though the use of several mathematical formulations is employed for FLP, Quadratic Assignment Problem (QAP) is one of the most commonly used. One of the major problems of Combinatorial NP-hard Optimization Problem is QAP mathematical model. Consequently, many approaches have been introduced to solve this problem, and these approaches are classified as Approximate and Exact methods. With QAP, each facility is allocated to just one location, thereby reducing cost in terms of aggregate distances weighted by flow values. The primary aim of this study is to propose a hybrid approach which combines Discrete Differential Evolution (DDE) algorithm and Tabu Search (TS) algorithm to enhance solutions of QAP model, to reduce the distances between the locations by finding the best distribution of N facilities to N locations, and to implement hybrid approach based on discrete differential evolution (HDDETS) on many instances of QAP from the benchmark. The performance of the proposed approach has been tested on several sets of instances from the data set of QAP and the results obtained have shown the effective performance of the proposed algorithm in improving several solutions of QAP in reasonable time. Afterwards, the proposed approach is compared with other recent methods in the literature review. Based on the computation results, the proposed hybrid approach outperforms the other methods.

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Section: Literature Reviewmentioning

confidence: 99%

A new hybrid approach based on discrete differential evolution algorithm to enhancement solutions of quadratic assignment problem

Hameed¹,

Aboobaider²,

Mutar³

et al. 2020

10.5267/j.ijiec

View full text Add to dashboard Cite

show abstract

“…A DE with Scale Factor Local Search was introduced in [23] and extended in [24] for self-adaptive DE schemes. The use of a tabu list in the DE has also been applied in recent works [25,26,27].…”

Section: Related Workmentioning

confidence: 99%

Enhanced parallel Differential Evolution algorithm for problems in computational systems biology

Penas

Banga

González

et al. 2015

Applied Soft Computing

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“…Recently, new QAP solution methodologies based on adaptation of powerful numerical optimization algorithms are presented. In this respect applications of particle swarm optimization (PSO) [45,46], differential evolution (DE) [47,48], imperialistic competitive algorithm (ICA) [49], and migrating birds optimization (MBO) algorithm [50] are reported to provide promising results compared to well-known metaheuristic algorithms for QAP. Among newly developed metaheuristic algorithms, chemical reaction optimization (CRO) has also been demonstrated to be a competitive algorithm for QAP and other difficult scheduling problems [51][52][53][54].…”

Section: The Quadratic Assignment Problemmentioning

confidence: 99%

A great deluge and tabu search hybrid with two-stage memory support for quadratic assignment problem

Acan

Ünveren

2015

Applied Soft Computing

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Solving quadratic assignment problems by differential evolution

Cited by 7 publications

References 9 publications

A new hybrid approach based on discrete differential evolution algorithm to enhancement solutions of quadratic assignment problem

A new hybrid approach based on discrete differential evolution algorithm to enhancement solutions of quadratic assignment problem

Enhanced parallel Differential Evolution algorithm for problems in computational systems biology

A great deluge and tabu search hybrid with two-stage memory support for quadratic assignment problem

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