Platform Resource Scheduling Method Based on Branch-and-Bound and Genetic Algorithm

Yanfen Zhang, Jinyao Ma (), Haibin Zhang () and Bin Yue
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Yanfen Zhang: Beijing University of Technology
Jinyao Ma: Beijing University of Technology
Haibin Zhang: Beijing University of Technology
Bin Yue: Beijing Aeronautical Technology Research Center

Annals of Data Science, 2023, vol. 10, issue 5, No 12, 1445 pages

Abstract: Abstract Platform resource scheduling is an operational research optimization problem of matching tasks and platform resources, which has important applications in production or marketing arrangement layout, combat task planning, etc. The existing algorithms are inflexible in task planning sequence and have poor stability. Aiming at this defect, the branch-and-bound algorithm is combined with the genetic algorithm in this paper. Branch-and-bound algorithm can adaptively adjust the next task to be planned and calculate a variety of feasible task planning sequences. Genetic algorithm is used to assign a platform combination to the selected task. Besides, we put forward a new lower bound calculation method and pruning rule. On the basis of the processing time of the direct successor tasks, the influence of the resource requirements of tasks on the priority of tasks is considered. Numerical experiments show that the proposed algorithm has good performance in platform resource scheduling problem.

Keywords: Platform resource scheduling; Branch-and-bound algorithm; Genetic algorithm; Task planning sequence; Lower bound; Pruning rule (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s40745-023-00470-8

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