FA–QABC–MRTA: a solution for solving the multi-robot task allocation problem

Farouq Zitouni, Ramdane Maamri, Saad Harous

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)

Abstract

The problem of task allocation in a multi-robot system is the situation where we have a set of tasks and a number of robots; then each task is assigned to the appropriate robots with the aim of optimizing some criteria subject to constraints, e.g., allocate the maximum number of tasks. We propose an effective solution to address this problem. It implements a two-stage methodology: first, a global allocation based of the well-known firefly algorithm, and then, a local allocation combining advantages of quantum genetic algorithms and artificial bee colony optimization. We compared our proposed solution to one solution from the state of the art. The simulation results show that our scheme significantly performs better than this solution. Our solution allocated 100 % of the tasks (in every configuration tried in the experiments) and enhanced the allocation time by 75 %.

Original languageEnglish
Pages (from-to)407-418
Number of pages12
JournalIntelligent Service Robotics
Volume12
Issue number4
DOIs
Publication statusPublished - Oct 1 2019

Keywords

  • Artificial bee colony optimization
  • Firefly algorithm
  • Multi-robot system
  • Quantum genetic algorithms
  • Task allocation

ASJC Scopus subject areas

  • Computational Mechanics
  • Engineering (miscellaneous)
  • Mechanical Engineering
  • Artificial Intelligence

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