Optimizing Task Allocation in Nuclear Accidents Rescue Response Using Particle Swarm Optimization

Boming Zhang, Zhihong Peng

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The environment after the nuclear power accident is complex, and it is difficult for rescue workers to enter the accident area safely and effectively rescue the survivors. The robot can replace the rescue workers to complete the rescue work efficiently. On this basis, a task allocation method for emergency multi-robot after nuclear power accident is proposed. First, according to the position and time window constraints of the task, a task sequencing method is proposed, and the inferior solution is eliminated according to the robot's ability constraints when generating the initial solution, so as to reduce the computational complexity. Then, considering that the task and robot number are nominal variables and discrete, a particle swarm optimization iteration method based on roulette wheel is used to solve the task assignment problem based on grouping. The experimental results show that this method can effectively shorten the rescue path and speed up the generation of task assignment scheme.

Original languageEnglish
Title of host publication2023 42nd Chinese Control Conference, CCC 2023
PublisherIEEE Computer Society
Pages1988-1993
Number of pages6
ISBN (Electronic)9789887581543
DOIs
Publication statusPublished - 2023
Event42nd Chinese Control Conference, CCC 2023 - Tianjin, China
Duration: 24 Jul 202326 Jul 2023

Publication series

NameChinese Control Conference, CCC
Volume2023-July
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference42nd Chinese Control Conference, CCC 2023
Country/TerritoryChina
CityTianjin
Period24/07/2326/07/23

Keywords

  • particle swarm optimization
  • rescue
  • roulette wheel selection
  • task allocation

Fingerprint

Dive into the research topics of 'Optimizing Task Allocation in Nuclear Accidents Rescue Response Using Particle Swarm Optimization'. Together they form a unique fingerprint.

Cite this