Cooperative multiple task assignment considering precedence constraints using multi-chromosome encoded genetic algorithm

Guangtong Xu, Li Liu, Teng Long*, Zhu Wang, Ming Cai

*Corresponding author for this work

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

17 Citations (Scopus)

Abstract

In the problem of cooperative multiple task assignment for heterogeneous unmanned aerial vehicles (UAVs), multiple consecutive tasks need to be performed on each target subject to task precedence constraints. An arbitrary task execution order might result in deadlock situations, i.e., one or multiple vehicles fall into an infinite waiting loop. In this paper, a multi-chromosome encoded genetic algorithm (MCE-GA) is proposed for avoiding the deadlock situations and assigning heterogeneous vehicles on multiple targets. The deadlock-free individuals are generated by considering the target identifiers and task precedence constraints in the multi-chromosome encoding process. Moreover, the specific crossover and mutation operators are designed to guarantee the feasibility of offspring individuals during the evolution process. The performance of MCE-GA is tested via comparing with random search method on simulation experiments. The comparison results from Monte Carlo simulations demonstrate that MCE-GA can produce better feasible solutions than random search method.

Original languageEnglish
Title of host publicationAIAA Guidance, Navigation, and Control
PublisherAmerican Institute of Aeronautics and Astronautics Inc, AIAA
ISBN (Print)9781624105265
DOIs
Publication statusPublished - 1 Jan 2018
EventAIAA Guidance, Navigation, and Control Conference, 2018 - Kissimmee, United States
Duration: 8 Jan 201812 Jan 2018

Publication series

NameAIAA Guidance, Navigation, and Control Conference, 2018

Conference

ConferenceAIAA Guidance, Navigation, and Control Conference, 2018
Country/TerritoryUnited States
CityKissimmee
Period8/01/1812/01/18

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