An ant colony hyperheuristic approach for matrix bandwidth reduction

Oliveira, Sanderson L. Gonzaga de; Silva, L.M.

doi:10.1016/j.asoc.2020.106434

Cited by 10 publications

(35 citation statements)

References 26 publications

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“…Therefore, when considering the execution times as a relevant aspect of the analysis, the resulting heuristics from the ACHH approach are the current state-of-the-art heuristics for bandwidth reduction. The present study extends the previous investigation [20]. Specifically, the hyper-heuristic approach proposed in the present study employs a local search procedure.…”

Section: Graph-theory Algorithmsmentioning

confidence: 53%

“…This research followed the current propensity for using a hyperheuristic approach in challenging problems, which are difficult to be solved through traditional strategies. Thus, previous publications [19,20] proposed an ant colony hyper-heuristic (ACHH) approach for the bandwidth reduction aiming at accelerating a linear system solver. The hyper-heuristic system was provided as input a small set of matrices arising from an application domain.…”

Section: Graph-theory Algorithmsmentioning

confidence: 99%

“…Many papers justified designing a new high-cost heuristic for reducing the bandwidth of matrices because it is relevant in engineering applications. However, application programmers, who proposed slow algorithms for the problem, were unfamiliar with the need for the heuristic to have a low computational cost to accelerate linear system solvers [20]. A previous publication [17] evaluated several heuristics for bandwidth reduction.…”

Section: Metaheuristic Algorithmsmentioning

confidence: 99%

“…Since the mid-1960s, practitioners have proposed heuristics for bandwidth reduction [5,16]. Previous publications [5,[16][17][18]20] have reviewed various heuristics and have indicated the most promising low-cost heuristics for bandwidth reduction so that they can be used in a preprocessing step when solving linear systems [20]. In this context, practical heuristics for bandwidth reduction compute at low cost and yield reasonable bandwidth results [16,17,20].…”

Section: Introductionmentioning

confidence: 99%

“…Hyper-heuristics operate on a search space of heuristics instead of searching on the domain of problem solutions. Specifically, this paper modifies an ant colony hyper-heuristic (ACHH) approach for evolving heuristics for the bandwidth reduction of matrices [19,20]. We applied the Hill-Climbing algorithm proposed by Lim et al [23].…”

Section: Introductionmentioning

confidence: 99%

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Low-cost heuristics for matrix bandwidth reduction combined with a Hill-Climbing strategy

Oliveira

Silva

2021

RAIRO-Oper. Res.

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This paper studies heuristics for the bandwidth reduction of large-scale matrices in serial computations. Bandwidth optimization is a demanding subject for a large number of scientific and engineering applications. A heuristic for bandwidth reduction labels the rows and columns of a given sparse matrix. The algorithm arranges entries with a nonzero coefficient as close to the main diagonal as possible. This paper modifies an ant colony hyper-heuristic approach to generate expert-level heuristics for bandwidth reduction combined with a Hill-Climbing strategy when applied to matrices arising from specific application areas. Specifically, this paper uses low-cost state-of-the-art heuristics for bandwidth reduction in tandem with a Hill-Climbing procedure. The results yielded on a wide-ranging set of standard benchmark matrices showed that the proposed strategy outperformed low-cost state-of-the-art heuristics for bandwidth reduction when applied to matrices with symmetric sparsity patterns.

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Section: Graph-theory Algorithmsmentioning

confidence: 53%

Section: Graph-theory Algorithmsmentioning

confidence: 99%

Section: Metaheuristic Algorithmsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Low-cost heuristics for matrix bandwidth reduction combined with a Hill-Climbing strategy

Oliveira

Silva

2021

RAIRO-Oper. Res.

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A Biased Random-Key Genetic Algorithm for Bandwidth Reduction

Silva

Brandão

Morais

et al. 2020

Computational Science and Its Applications – ICCSA 2020

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The bandwidth minimization problem is a well-known -hard problem. This paper describes our experience in implementing a biased random-key genetic algorithm for the bandwidth reduction problem. Specifically, this paper compares the results of the new algorithm with the results yielded by four approaches. The results obtained on a set of standard benchmark matrices taken from the SuiteSparse sparse matrix collection indicated that the novel approach did not compare favorably with the state-of-the-art metaheuristic algorithm for bandwidth reduction. The former seems to be faster than the latter. On the other hand, the design of heuristics for bandwidth reduction is a very consolidated research area. Thus, a paradigm shift seems necessary to design a heuristic with better results than the state-of-the-art meta-heuristic algorithm at shorter execution times.

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