Jumping particle swarm optimisation method for solving minimum weight vertex cover problem

Balaji, S.; Vikram, S.T.; Kanagasabapathy, G.

doi:10.1504/ijbic.2021.119198

Cited by 3 publications

(1 citation statement)

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“…The intelligent algorithm of heuristic thought usually refers to the algorithm that people construct according to natural phenomenon, social experience, or biological inspiration, and then by summarizing simulation innovation. The idea is that when addressing multi-constraint problems, a feasible solution can be given to satisfy multiple objective optimizations [50] as far as possible. The focus is on multi-objective optimization [51][52][53], for each instance, the solution obtained now is not the optimal solution for a single objective, but the best solution under the condition of satisfying the requirements of multiple objectives as far as possible.…”

Section: Scheduling Algorithmmentioning

confidence: 99%

Survey on Task Scheduling Optimization Strategy under Multi-Cloud Environment

Zhang¹,

Geng²,

Cai³

2023

Computer Modeling in Engineering &Amp; Sciences

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Cloud computing technology is favored by users because of its strong computing power and convenient services. At the same time, scheduling performance has an extremely efficient impact on promoting carbon neutrality. Currently, scheduling research in the multi-cloud environment aims to address the challenges brought by business demands to cloud data centers during peak hours. Therefore, the scheduling problem has promising application prospects under the multi-cloud environment. This paper points out that the currently studied scheduling problems in the multi-cloud environment mainly include independent task scheduling and workflow task scheduling based on the dependencies between tasks. This paper reviews the concepts, types, objectives, advantages, challenges, and research status of task scheduling in the multi-cloud environment. Task scheduling strategies proposed in the existing related references are analyzed, discussed, and summarized, including research motivation, optimization algorithm, and related objectives. Finally, the research status of the two kinds of task scheduling is compared, and several future important research directions of multi-cloud task scheduling are proposed.

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Section: Scheduling Algorithmmentioning

confidence: 99%

Survey on Task Scheduling Optimization Strategy under Multi-Cloud Environment

Zhang¹,

Geng²,

Cai³

2023

Computer Modeling in Engineering &Amp; Sciences

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A Swarm Intelligence Technique for Link Monitoring Problems in Wireless Ad Hoc Networks

Maheswari,

Balaji

2024

Natl. Acad. Sci. Lett.

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Multi-UAV Cooperative Trajectory Planning Based on Many-Objective Evolutionary Algorithm

Bai

Fan

et al. 2022

Complex Syst. Model. Simul.

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The trajectory planning of multiple unmanned aerial vehicles (UAVs) is the core of efficient UAV mission execution. Existing studies have mainly transformed this problem into a single-objective optimization problem using a single metric to evaluate multi-UAV trajectory planning methods. However, multi-UAV trajectory planning evolves into a many-objective optimization problem due to the complexity of the demand and the environment. Therefore, a multi-UAV cooperative trajectory planning model based on many-objective optimization is proposed to optimize trajectory distance, trajectory time, trajectory threat, and trajectory coordination distance costs of UAVs. The NSGA-III algorithm, which overcomes the problems of traditional trajectory planning, is used to solve the model. This paper also designs a segmented crossover strategy and introduces dynamic crossover probability in the crossover operator to improve the solving efficiency of the model and accelerate the convergence speed of the algorithm. Experimental results prove the effectiveness of the multi-UAV cooperative trajectory planning algorithm, thereby addressing different actual needs.

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Jumping particle swarm optimisation method for solving minimum weight vertex cover problem

Cited by 3 publications

References 0 publications

Survey on Task Scheduling Optimization Strategy under Multi-Cloud Environment

Survey on Task Scheduling Optimization Strategy under Multi-Cloud Environment

A Swarm Intelligence Technique for Link Monitoring Problems in Wireless Ad Hoc Networks

Multi-UAV Cooperative Trajectory Planning Based on Many-Objective Evolutionary Algorithm

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