Title:
TASK SCHEDULING METHOD BASED ON IMPROVED PARTICLE SWARM OPTIMIZATION ALGORITHM
Document Type and Number:
WIPO Patent Application WO/2024/074023
Kind Code:
A1
Abstract:
Disclosed in the present invention is a task scheduling method based on an improved particle swarm optimization algorithm. The method comprises the following steps: acquiring task data to be scheduled, and coding particles according to the task data; performing iterative calculation on the particles by means of a particle swarm optimization algorithm; if the particle swarm optimization algorithm does not fall into a local optimal solution, directly outputting a scheduling scheme; and if the particle swarm optimization algorithm falls into the local optimal solution, outputting a scheduling scheme by means of fusing the particle swarm optimization algorithm with a Cuckoo search algorithm. When a particle swarm optimization algorithm falls into a local optimal solution, a Cuckoo search algorithm is introduced, such that the predicament in which the particle swarm optimization algorithm falls into the local optimal solution is solved, and the global search capability of the algorithm is also improved.
Inventors:
ZHANG DENGYIN (CN)
JI MAOMAO (CN)
ZHAO YING (CN)
JI MAOMAO (CN)
ZHAO YING (CN)
Application Number:
PCT/CN2023/086264
Publication Date:
April 11, 2024
Filing Date:
April 04, 2023
Export Citation:
Assignee:
UNIV NANJING POSTS & TELECOMMUNICATIONS (CN)
International Classes:
G06F9/48; G06F9/50; G06N3/00
Foreign References:
| CN115454611A | 2022-12-09 | |||
| CN106295886A | 2017-01-04 | |||
| CN107437813A | 2017-12-05 | |||
| CN108520284A | 2018-09-11 | |||
| US20210224576A1 | 2021-07-22 |
Attorney, Agent or Firm:
SHENZHEN ELSON PATENT AGENT FIRM (GENERAL PARTNERSHIP) et al. (CN)
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