A local search algorithm with reinforcement learning based repair procedure for minimum weight independent dominating set

Wang, Yiyuan; Pan, Shiwei; Li, Chenxi; Yin, Minghao

doi:10.1016/j.ins.2019.09.059

Cited by 17 publications

(9 citation statements)

References 16 publications

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“…An efficient algorithm that has linear time complexity [25] was designed specifically for series-parallel graphs. Wang et al [132] proposed to combine a local search algorithm with the LSRR (stands for reinforcement-learning-based repair procedure) to address this problem. They gave three scoring functions in considering both vertex and edge weights, and presented a method to improve local search based on reinforcement learning (RL).…”

Section: Dominating Setmentioning

confidence: 99%

“…A RL mechanism is designed to select vertices that need to be added into S based on the searching history, after some vertices in S are removed by using a frequency technique. The four important concepts in RL, state, action, transition and reward, are defined accordingly (see [132] for further details). Specifically, the reward function is divided into positive and negative rewards after the local search is implemented, depending whether a vertex belongs to the local best solution.…”

Section: Dominating Setmentioning

confidence: 99%

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Learning-Based Approaches for Graph Problems: A Survey

Yow¹,

Luo²

2022

Preprint

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Over the years, many graph problems specifically those in NP-complete are studied by a wide range of researchers. Some famous examples include graph colouring, travelling salesman problem and subgraph isomorphism. Most of these problems are typically addressed by exact algorithms, approximate algorithms and heuristics. There are however some drawback for each of these methods. Recent studies have employed learning-based frameworks such as machine learning techniques in solving these problems, given that they are useful in discovering new patterns in structured data that can be represented using graphs. This research direction has successfully attracted a considerable amount of attention. In this survey, we provide a systematic review mainly on classic graph problems in which learning-based approaches have been proposed in addressing the problems. We discuss the overview of each framework, and provide analyses based on the design and performance of the framework. Some potential research questions are also suggested. Ultimately, this survey gives a clearer insight and can be used as a stepping stone to the research community in studying problems in this field.

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Section: Dominating Setmentioning

confidence: 99%

Section: Dominating Setmentioning

confidence: 99%

Learning-Based Approaches for Graph Problems: A Survey

Yow¹,

Luo²

2022

Preprint

View full text Add to dashboard Cite

show abstract

“…The decoder in the algorithm can transform any real value vector into an effective solution to the problem. Recently, a local search algorithm with a reinforcement learning-based repair procedure was designed [14], which combines the idea of reinforcement learning, local search and repair process to improve the solution of the MWIDS.…”

Section: D E B Amentioning

confidence: 99%

Improved Memetic Algorithm for Solving the Minimum Weight Vertex Independent Dominating Set

Zhou

Liu

et al. 2020

Mathematics

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The minimum weight vertex independent dominating set (MWVIDS) problem is an important version of the minimum independent dominating set. The MWVIDS problem has a number of applications in many fields. However, the MWVIDS problem is known to be NP-hard and thus computationally challenging. In this work, we present the improved memetic algorithm called MSSAS for solving the MWVIDS problem. The proposed MSSAS algorithm combines probability-based dynamic optimization (PDO) (to generate good and diverse offspring solutions by assembling elements of existing good solutions) as well as a local search phase named C_LS (to seek high-quality local optima by combining the idea of constrained-based two-level configuration checking strategy and tabu mechanism). The extensive results on popular DIMACS and BHOLIB benchmarks demonstrate that MSSAS competes favorably with the state-of-the-art algorithms. In addition, we analyze the benefits of the newly raised components including two above proposed ideas with our memetic framework. It is worth mentioning that the combination of both components has excellent effects for the MWVIDS problem.

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“…The node-weighted versions of these problems are also often considered. The latest algorithms for the minimum weight (vertex) independent dominating set problem include a local search approach that makes use of a reinforcement learning based repair procedure [17] and a memetic algorithm [18]. Next, it is worth mentioning the so-called minimum total dominating set problem, which was solved by means of a hybrid evolutionary algorithm in [19].…”

Section: Literature Review On Related Problemsmentioning

confidence: 99%

Barrakuda: A Hybrid Evolutionary Algorithm for Minimum Capacitated Dominating Set Problem

Pinacho-Davidson

Blum

2020

Mathematics

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The minimum capacitated dominating set problem is an NP-hard variant of the well-known minimum dominating set problem in undirected graphs. This problem finds applications in the context of clustering and routing in wireless networks. Two algorithms are presented in this work. The first one is an extended version of construct, merge, solve and adapt, while the main contribution is a hybrid between a biased random key genetic algorithm and an exact approach which we labeled BARRAKUDAmathsizesmall. Both algorithms are evaluated on a large set of benchmark instances from the literature. In addition, they are tested on a new, more challenging benchmark set of larger problem instances. In the context of the problem instances from the literature, the performance of our algorithms is very similar. Moreover, both algorithms clearly outperform the best approach from the literature. In contrast, BARRAKUDAmathsizesmall is clearly the best-performing algorithm for the new, more challenging problem instances.

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A local search algorithm with reinforcement learning based repair procedure for minimum weight independent dominating set

Cited by 17 publications

References 16 publications

Learning-Based Approaches for Graph Problems: A Survey

Learning-Based Approaches for Graph Problems: A Survey

Improved Memetic Algorithm for Solving the Minimum Weight Vertex Independent Dominating Set

Barrakuda: A Hybrid Evolutionary Algorithm for Minimum Capacitated Dominating Set Problem

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