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Multi Agent Collaborative Search

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NEO 2015

Part of the book series: Studies in Computational Intelligence ((SCI,volume 663))

Abstract

This chapter presents an overview of Multi Agent Collaborative Search (MACS), for multi-objective optimisation with an analysis of different heuristics for local search. In particular the effects of simple inertia and differential evolution operators in combination with pattern search and gradient methods are investigated. Different benchmarks are used to demonstrate the effectiveness of the MACS framework and of the heuristics for both local and global search. The MACS framework is tested on two sets of academic problems and two real space mission design problems using the IGD and the success rate as performance metrics. The performance of MACS is compared against three known multi-objective optimisation algorithms: NSGA-II, MOAED and MTS.

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Author information

Authors and Affiliations

  1. Department of Mechanical and Aerospace Engineering, University of Strathclyde, Glasgow, UK

    Massimiliano Vasile & Lorenzo Ricciardi

Authors
  1. Massimiliano Vasile
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  2. Lorenzo Ricciardi
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Corresponding author

Correspondence to Massimiliano Vasile .

Editor information

Editors and Affiliations

  1. Departamento de Comput Cinvestav-IPN, Mexico, Mexico

    Oliver Schütze

  2. Posgrado en Ciencias de la Ingeniería, Instituto Tecnológico de Tijuana, Tijuana, Baja California, Mexico

    Leonardo Trujillo

  3. Université de Bordeaux, Bordeaux, France

    Pierrick Legrand

  4. Posgrado en Ciencias de la Ingeniería, Instituto Tecnológico de Tijuana, Tijuana, Mexico

    Yazmin Maldonado

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© 2017 Springer International Publishing Switzerland

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Vasile, M., Ricciardi, L. (2017). Multi Agent Collaborative Search. In: Schütze, O., Trujillo, L., Legrand, P., Maldonado, Y. (eds) NEO 2015. Studies in Computational Intelligence, vol 663. Springer, Cham. https://doi.org/10.1007/978-3-319-44003-3_10

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  • DOI: https://doi.org/10.1007/978-3-319-44003-3_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-44002-6

  • Online ISBN: 978-3-319-44003-3

  • eBook Packages: EngineeringEngineering (R0)

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