An artificial bee colony algorithm for minimum weight dominating set

Nitash, C G; Singh, Alok

doi:10.1109/sis.2014.7011811

Cited by 10 publications

(6 citation statements)

References 18 publications

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“…Specially, the first strategy is greedy and adds a vertex by using score 2 , while the second strategy adds a vertex into the candidate solution randomly. ABC (Nitash & Singh, 2014) prunes some redundant vertices according to the greedy strategy score 1 . In EA/G-IR (Chaurasia & Singh, 2015), there are two modifications in score 2 .…”

Section: The Previous Scoring Function For Mwdsmentioning

confidence: 99%

“…A hybrid steady-state genetic algorithm HGA is proposed by using binary tournament selection method, fitness-based crossover and a simple bit-flip mutation scheme (Potluri & Singh, 2013). In the work of Nitash and Singh (2014), a swarm intelligence algorithm called ABC uses an artificial bee colony method to solve MWDS. A hybrid approach EA/G-IR is presented, which combines an evolutionary algorithm with guided mutation and an improvement operator (Chaurasia & Singh, 2015).…”

Section: Introductionmentioning

confidence: 99%

“…Four greedy algorithms for the MWDS problem are developed by using four different scoring functions (Potluri & Singh, 2013). After that, some scoring functions have been proposed recently (Potluri & Singh, 2013;Nitash & Singh, 2014;Chaurasia & Singh, 2015;Bouamama & Blum, 2016). These functions are mostly designed based on the information of the graph itself, for example vertex degree and vertex uncovered neighbour weight.…”

Section: Introductionmentioning

confidence: 99%

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Local Search for Minimum Weight Dominating Set with Two-Level Configuration Checking and Frequency Based Scoring Function

Wang¹,

Cai²,

Yin³

2017

jair

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The Minimum Weight Dominating Set (MWDS) problem is an important generalization of the Minimum Dominating Set (MDS) problem with extensive applications. This paper proposes a new local search algorithm for the MWDS problem, which is based on two new ideas. The first idea is a heuristic called two-level configuration checking (CC 2 ), which is a new variant of a recent powerful configuration checking strategy (CC) for effectively avoiding the recent search paths. The second idea is a novel scoring function based on the frequency of being uncovered of vertices. Our algorithm is called CC 2 FS, according to the names of the two ideas. The experimental results show that, CC 2 FS performs much better than some state-of-the-art algorithms in terms of solution quality on a broad range of MWDS benchmarks.

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Section: The Previous Scoring Function For Mwdsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Local Search for Minimum Weight Dominating Set with Two-Level Configuration Checking and Frequency Based Scoring Function

Wang¹,

Cai²,

Yin³

2017

jair

View full text Add to dashboard Cite

show abstract

“…Minimum weight dominating set problem (MWDS) on undirected graphs is a widely-studied problem, and many approaches (Albuquerque and Vidal, 2018;Lin and Guan, 2018;Wang et al, 2018;Lin et al, 2016;Chaurasia and Singh, 2015a;Nitash and Singh, 2014;Potluri and Singh, 2013;Jovanovic et al, 2010;Shetgaonkar and Singh, 2020) have been proposed in the literature for this problem. However, the corresponding problem in directed graphs, viz.…”

Section: Introductionmentioning

confidence: 99%

Swarm intelligence, exact and matheuristic approaches for minimum weight directed dominating set problem

Nakkala

Singh

Rossi

2022

Engineering Applications of Artificial Intelligence

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“…For SCP, there are complete algorithms (Caprara, Toth, and Fischetti 2000), genetic algorithm (Beasley and Chu 1996), simulated annealing (Jacobs and Brusco 1995) and local search algorithm (Gao, Weise, and Li 2014). For DSP, there are ant colony optimization (ACO) (Jovanovic et al 2010), swarm intelligence algorithm (Nitash and Singh 2014) and local search algorithm (Wang et al 2018).…”

Section: Introductionmentioning

confidence: 99%

Solving Set Cover and Dominating Set via Maximum Satisfiability

Lei

2020

AAAI

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The Set Covering Problem (SCP) and Dominating Set Problem (DSP) are NP-hard and have many real world applications. SCP and DSP can be encoded into Maximum Satisfiability (MaxSAT) naturally and the resulting instances share a special structure. In this paper, we develop an efficient local search solver for MaxSAT instances of this kind. Our algorithm contains three phrase: construction, local search and recovery. In construction phrase, we simplify the instance by three reduction rules and construct an initial solution by a greedy heuristic. The initial solution is improved during the local search phrase, which exploits the feature of such instances in the scoring function and the variable selection heuristic. Finally, the corresponding solution of original instance is recovered in the recovery phrase. Experiment results on a broad range of large scale instances of SCP and DSP show that our algorithm significantly outperforms state of the art solvers for SCP, DSP and MaxSAT.

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An artificial bee colony algorithm for minimum weight dominating set

Cited by 10 publications

References 18 publications

Local Search for Minimum Weight Dominating Set with Two-Level Configuration Checking and Frequency Based Scoring Function

Local Search for Minimum Weight Dominating Set with Two-Level Configuration Checking and Frequency Based Scoring Function

Swarm intelligence, exact and matheuristic approaches for minimum weight directed dominating set problem

Solving Set Cover and Dominating Set via Maximum Satisfiability

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