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Intelligent Service Robotics

, Volume 12, Issue 4, pp 407–418 | Cite as

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

  • Farouq ZitouniEmail author
  • Ramdane Maamri
  • Saad Harous
Original Research Paper
  • 70 Downloads

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 \(75\%\).

Keywords

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

Notes

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Computer ScienceKasdi Merbah UniversityOuarglaAlgeria
  2. 2.Department of Computer ScienceConstantine 2 - Abdelhamid Mehri UniversityConstantineAlgeria
  3. 3.Department of Computer ScienceUAE UniversityAbu DhabiUnited Arab Emirates

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