Soft Computing

, Volume 21, Issue 17, pp 4883–4900 | Cite as

Solving complex multi-UAV mission planning problems using multi-objective genetic algorithms

  • Cristian Ramirez-AtenciaEmail author
  • Gema Bello-Orgaz
  • María D. R-Moreno
  • David Camacho


Due to recent booming of unmanned air vehicles (UAVs) technologies, these are being used in many fields involving complex tasks. Some of them involve a high risk to the vehicle driver, such as fire monitoring and rescue tasks, which make UAVs excellent for avoiding human risks. Mission planning for UAVs is the process of planning the locations and actions (loading/dropping a load, taking videos/pictures, acquiring information) for the vehicles, typically over a time period. These vehicles are controlled from ground control stations (GCSs) where human operators use rudimentary systems. This paper presents a new multi-objective genetic algorithm for solving complex mission planning problems involving a team of UAVs and a set of GCSs. A hybrid fitness function has been designed using a constraint satisfaction problem to check whether solutions are valid and Pareto-based measures to look for optimal solutions. The algorithm has been tested on several datasets, optimizing different variables of the mission, such as the makespan, the fuel consumption, and distance. Experimental results show that the new algorithm is able to obtain good solutions; however, as the problem becomes more complex, the optimal solutions also become harder to find.


Unmanned air vehicles Mission planning Multi-objective optimization Genetic algorithms Constraint satisfaction problems 



The authors would like to acknowledge the support obtained from Airbus Defence & Space, specially from Savier Open Innovation project members: José Insenser, César Castro, Gemma Blasco, and Inés Moreno. This study was funded by Spanish Ministry of Science and Education and Competitivity and European Regional Development Fund FEDER (TIN2014-56494-C4-4-P), Comunidad Autónoma de Madrid (CIBERDINE S2013/ICE-3095), and Airbus Defence & Space under Savier Project (FUAM-076915).

Compliance with ethical standards

Conflict of interest

The Authors: Cristian Ramirez-Atencia, Gema Bello-Orgaz, Maria D. R-Moreno, and David Camacho declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Cristian Ramirez-Atencia
    • 1
    Email author
  • Gema Bello-Orgaz
    • 1
  • María D. R-Moreno
    • 2
  • David Camacho
    • 1
  1. 1.Universidad Autonónoma de MadridMadridSpain
  2. 2.Universidad de AlcaláMadridSpain

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