An algorithm based on ant colony optimization for the minimum connected dominating set problem

Bouamama, Salim; Blum, Christian; Fages, Jean-Guillaume

doi:10.1016/j.asoc.2019.04.028

Cited by 39 publications

(21 citation statements)

References 26 publications

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“…The addition-based method has two versions. The first version, used in ACO-RVNS (Bouamama et al, 2019) and in MCDS/TS (Morgan & Grout, 2007), works as follows: during each iteration, the algorithm starts from an empty candidate solution D, and iteratively adds a vertex from N (D) to D until D becomes a feasible solution. The second version, used in GRASP (Li et al, 2017) and MSLS (Li et al, 2019), works as follows: the algorithm allows removing articulation vertices of D, so D may become disconnected.…”

Section: Previous Connectivity Maintenance Methodsmentioning

confidence: 99%

“…Li et al presented a multi-start local search algorithm called MSLS based on three mechanisms including a vertex score, configuration checking, and vertex flipping (Li et al, 2019). Finally, a meta-heuristic algorithm called ACO-RVNS (Bouamama et al, 2019) was proposed, based on ant colony optimization and reduced variable neighborhood search. Moreover, ACO-RVNS has also been applied to weighted version of MCDS problem.…”

Section: Previous Workmentioning

confidence: 99%

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Efficient Local Search based on Dynamic Connectivity Maintenance for Minimum Connected Dominating Set

Zhang¹,

Li²,

Wang³

2021

jair

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The minimum connected dominating set (MCDS) problem is an important extension of the minimum dominating set problem, with wide applications, especially in wireless networks. Most previous works focused on solving MCDS problem in graphs with relatively small size, mainly due to the complexity of maintaining connectivity. This paper explores techniques for solving MCDS problem in massive real-world graphs with wide practical importance. Firstly, we propose a local greedy construction method with reasoning rule called 1hopReason. Secondly and most importantly, a hybrid dynamic connectivity maintenance method (HDC+) is designed to switch alternately between a novel fast connectivity maintenance method based on spanning tree and its previous counterpart. Thirdly, we adopt a two-level vertex selection heuristic with a newly proposed scoring function called chronosafety to make the algorithm more considerate when selecting vertices. We design a new local search algorithm called FastCDS based on the three ideas. Experiments show that FastCDS significantly outperforms five state-of-the-art MCDS algorithms on both massive graphs and classic benchmarks.

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Section: Previous Connectivity Maintenance Methodsmentioning

confidence: 99%

Section: Previous Workmentioning

confidence: 99%

Efficient Local Search based on Dynamic Connectivity Maintenance for Minimum Connected Dominating Set

Zhang¹,

Li²,

Wang³

2021

jair

View full text Add to dashboard Cite

show abstract

“…Application practice proves that the optimization effect of the Ant Week algorithm is significantly better than the other two algorithms. The reason is analyzed because the Ant Week algorithm uses global feedback information in the search process, while the ant secret and ant quantity algorithms use local feedback information [28][29][30].…”

Section: Ant Colony Optimization Algorithm Principlementioning

confidence: 99%

Actuator Weak Fault Diagnosis in Autonomous Underwater Vehicle Based on Tri-Stable Stochastic Resonance

Yang

Guo

et al. 2020

Applied Sciences

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The autonomous underwater vehicle (AUV) is mainly used in the development and exploration of the ocean. As an important module of the AUV, the actuator plays an important role in the normal execution of the AUV. Therefore, the fault diagnosis of the actuator is particularly important. At present, the research on the strong faults, such as the winding of the actuator, has achieved good results, but the research on the weak fault diagnosis is relatively rare. In this paper, the tri-stable stochastic resonance model is analyzed, and the ant colony tri-stable stochastic resonance model is used to diagnose the weak fault. The system accurately diagnoses the fault of the actuator collision and verifies the adaptive tri-stable stochastic resonance system. This model has better diagnostic results than the bi-stable stochastic resonance system.

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“…Besides, evolutionary algorithms inspired by biological evolution are primarily suited for numerical optimization problems because they often found well approximating solutions for all types of challenges. In the recent years, numerous types of these schemes have been introduced by scientists and researchers, to name but a few, genetic algorithm [39], particle swarm optimization [40], ant colony [36], artificial bee colony [37], bat algorithm [38], firefly algorithm [46], grey wolf optimizer [47], invasive weed optimization [48], shuffled frog leaping algorithm [49], spider algorithm [50], whale optimization algorithm [51] and team game algorithm [52].…”

Section: Introductionmentioning

confidence: 99%

Numerical analysis of the Volterra differential equations via a combination of evolutionary algorithms with moving least squares and finite difference methods

Mahmoodabadi

2021

J. eng.

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In this paper, the Volterra differential equations governing on the predator-prey dynamics is numerically solved through the combination of evolutionary algorithms with Moving Least Squares as well as the Finite Difference Method. Among the numerous evolutionary algorithms, the Genetic Algorithms and Particle Swarm Optimization, as two powerful and effective approaches, are selected. The penalty method is chosen to impose the initial conditions on the objective function, while the Moving Least Squares is implemented to interpolate the derivatives in the differential equations. In order to illustrate the effectiveness of the Moving Least Squares, the results are compared with those obtained via the Finite Difference Method based evolutionary algorithms. Moreover, the results are associated with those of a numerical method and an analytical scheme to evaluate the obtained populations of the prey and the predator. These comparisons clearly illustrate the reliability and efficiency of the proposed methodology to solve nonlinear differential equations. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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An algorithm based on ant colony optimization for the minimum connected dominating set problem

Cited by 39 publications

References 26 publications

Efficient Local Search based on Dynamic Connectivity Maintenance for Minimum Connected Dominating Set

Efficient Local Search based on Dynamic Connectivity Maintenance for Minimum Connected Dominating Set

Actuator Weak Fault Diagnosis in Autonomous Underwater Vehicle Based on Tri-Stable Stochastic Resonance

Numerical analysis of the Volterra differential equations via a combination of evolutionary algorithms with moving least squares and finite difference methods

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