Ant colony optimisation with local search for the bandwidth minimisation problem on graphs

Guan, Jian; Li, Geng; Feng, Hui Bin

doi:10.1504/ijiids.2019.102327

Cited by 2 publications

(3 citation statements)

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“…The development of metaheuristic algorithms for bandwidth reduction began in the 1990s (Chagas & Gonzaga de Oliveira, 2015). Researchers have designed heuristics with the most different metaheuristics, including GRASP-PR (Piñana et al, 2004), genetic algorithm (Lim et al, 2006Czibula et al, 2013;Pop et al, 2014), simulated annealing (Rodriguez-Tello et al, 2008Torres-Jimenez et al, 2015), ant colony optimization (Kaveh & Sharafi, 2009;Pintea et al, 2010Pintea et al, , 2012Czibula et al, 2013;Guan et al, 2019;Gonzaga de Oliveira & Silva, 2019, variable neighborhood search (Mladenovic et al, 2010), genetic programming (Koohestani & Poli, 2011, charged system search algorithm (Kaveh & Sharafi, 2012), colliding bodies optimization (Kaveh & Bijari, 2015), brain storm optimization (Mafteiu-Scai et al, 2017, biased random-key genetic algorithm (Silva et al, 2020), and iterated local search (Gonzaga de Oliveira & Carvalho, 2022).…”

Section: Metaheuristic Algorithmsmentioning

confidence: 99%

An Evaluation of Heuristic Methods for the Bandwidth Reduction of Large-Scale Graphs

Gonzaga de Oliveira

2023

Pesqui. Oper.

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This paper studies the bandwidth reduction problem for large-scale sparse matrices in serial computations. A heuristic for bandwidth reduction reorders the rows and columns of a given sparse matrix, placing entries with a non-null value as close to the main diagonal as possible. Recently, a paper proposed the FNCHC+ heuristic. The heuristic method is a variant of the Fast Node Centroid Hill-Climbing algorithm. The FNCHC+ heuristic presented better results than the other existing heuristics in the literature when applied to reduce the bandwidth of large-scale graphs (of the underline matrices) with sizes up to 18.6 million vertices and up to 57.2 million edges. The present paper provides new experiments with even larger graphs. Specifically, the present study performs experiments with test problems containing up to 24 million vertices and 130 million edges. The results confirm that the FNCHC+ algorithm is the state-of-the-art metaheuristic algorithm for reducing the bandwidth of large-scale matrices.

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Section: Metaheuristic Algorithmsmentioning

confidence: 99%

An Evaluation of Heuristic Methods for the Bandwidth Reduction of Large-Scale Graphs

Gonzaga de Oliveira

2023

Pesqui. Oper.

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“…Thammano and Onnsrikaw [18] improved the strength of the ACO and employed one or other of four algorithms such as simulated annealing (SA), similarity measure SA (Sim-SA), 2-Opt and 3-Opt to find near-optimal solutions and improving local search. Guan et al [19] suggested an ACO with a local search for the bandwidth minimization problem on graphs. The primary novelty for this algorithm is the utilization of an efficient local search to increase ACO's intensification ability.…”

Section: Improvement By Applying Local Searchmentioning

confidence: 99%

“…• Find near-optimal solutions and improving local search. -ACO with local search for the bandwidth minimization problem on graphs [19].…”

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confidence: 99%

Recent research in finding the optimal path by ant colony optimization

Sari

Mohamad

2021

Bulletin EEI

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The computation of the optimal path is one of the critical problems in graph theory. It has been utilized in various practical ranges of real world applications including image processing, file carving and classification problem. Numerous techniques have been proposed in finding optimal path solutions including using ant colony optimization (ACO). This is a nature-inspired metaheuristic algorithm, which is inspired by the foraging behavior of ants in nature. Thus, this paper study the improvement made by many researchers on ACO in finding optimal path solution. Finally, this paper also identifies the recent trends and explores potential future research directions in file carving.

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Ant colony optimisation with local search for the bandwidth minimisation problem on graphs

Cited by 2 publications

References 0 publications

An Evaluation of Heuristic Methods for the Bandwidth Reduction of Large-Scale Graphs

An Evaluation of Heuristic Methods for the Bandwidth Reduction of Large-Scale Graphs

Recent research in finding the optimal path by ant colony optimization

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