A modified bat algorithm for the Quadratic Assignment Problem

Shukla, Apurv

doi:10.1109/cec.2015.7256929

Cited by 14 publications

(15 citation statements)

References 16 publications

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“…We compare our proposed algorithm with one recently reported by [12]. Table 3 summarizes the comparison of error rate of the proposed algorithm with bat algorithm and particle swarm optimization.…”

Section: Experiments and Resultsmentioning

confidence: 99%

Enhanced Cuckoo Search Algorithm with SPV Rule for Quadratic Assignment Problem

Ismail¹,

Hezam²,

El-Sharkawy³

2017

IJCA

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Cuckoo Search (CS) algorithm has exhibited good performance across a wide range of application problems. In this paper, a Modified Cuckoo Search (MCS) algorithm is presented to solve the Quadratic Assignment Problem (QAP), which is a NP-hard problem and is one of the most interesting and challenging combinatorial optimization problems in the research community. To handle the discrete variables of the Quadratic Assignment Problems, the smallest position value (SPV) rule is used to enable the continuous inter-species cuckoo search to be applied to most types of sequencing problems. In the computational experiments, we evaluate the performance of our approach on widely known instances from the literature. In these experiments, we compare the proposed algorithm against the best proposals from the related literature and we conclude that our algorithm is able to report highquality solutions.

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Section: Experiments and Resultsmentioning

confidence: 99%

Enhanced Cuckoo Search Algorithm with SPV Rule for Quadratic Assignment Problem

Ismail¹,

Hezam²,

El-Sharkawy³

2017

IJCA

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“…BA use of hill climbing for further intensification was done in the implementation in Reference 38. The BA is a computationally efficient algorithm that has shown promising results in tests done in Reference 38. It will be interesting to see how this algorithm would compete against other meta‐heuristic algorithms as it was only tested against PSO in Reference 38.…”

Section: Literature Reviewmentioning

confidence: 99%

A performance study of meta‐heuristic approaches for quadratic assignment problem

Achary

Pillay

Pillai

et al. 2021

Concurrency and Computation

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The quadratic assignment problem (QAP) is a well‐known challenging combinatorial optimization problem that has received many researchers' attention with varied real‐world and industrial applications areas. It is noteworthy to mention that a plethora of nature‐inspired optimization algorithms have successfully been used to solve various optimization problems, including several variants of the QAPs. In this article, a comprehensive literature review is presented to show the most relevant nature‐inspired algorithms that have been used in solving the QAP. More so, extensive experiments are conducted and analyzed to show the performance of the well‐known state‐of‐the‐art nature‐inspired meta‐heuristic optimization algorithms in solving the QAP, including the ant colony optimization (ACO), bat algorithm, genetic algorithm (GA), particle swarm optimization (PSO), and tabu search algorithm. Besides, a modified variant of the discrete PSO algorithm is implemented and compared with existing approaches. The six selected algorithms' performances, including the modified PSO, are validated on eight commonly used QAP instances of varying complexity and size, considering the quality of solutions achieved and computational time consumed by the representative algorithms. The numerical results revealed that the most competitive algorithm was ACO, while the GA appeared to be the worst performed algorithm among the six compared meta‐heuristic algorithms. However, based on the extensive analysis conducted on the tested algorithms, further improvements are suggested, including implementing new modified versions of the tested algorithms to tackle the QAP and its variant instances.

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“…This development was also aimed at solving the QAP. Also, in (Shukla, 2015) the Bat Algorithm (BA) was used for the same purpose. Similarly, the study conducted by Riffi et al (2017) aimed at enhancing the BA search strategy by introducing a new method.…”

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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A modified bat algorithm for the Quadratic Assignment Problem

Cited by 14 publications

References 16 publications

Enhanced Cuckoo Search Algorithm with SPV Rule for Quadratic Assignment Problem

Enhanced Cuckoo Search Algorithm with SPV Rule for Quadratic Assignment Problem

A performance study of meta‐heuristic approaches for quadratic assignment problem

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

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