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Distributed Computing and Artificial Intelligence pp 463–470Cite as

Multi-Objective Evolutionary Algorithms Used in Greenhouse Planning for Recycling Biomass into Energy

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Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 79))

Abstract

Advanced parallel Multi-Objective Evolutionary Algorithms (MOEA) have been used in order to solve a wide array of problems, including the planning of greenhouse crops. This paper shows the application of MOEA using the Island Parallel Model to solve a problem involving greenhouse crop planning in order to maximize profits and the production of biomass while reducing economic risks. The interest in maximizing biomass waste lies in the possibility of recycling it into heat and energy.

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Author information

Authors and Affiliations

  1. Dpt. of Computer Architecture and Electronics, University of Almería, Spain

    A. L. Márquez, C. Gil, A. Fernández & R. Baños

  2. Dpt. of Rural Engineering, University of Almería, Spain

    F. Manzano-Agugliaro & F. G. Montoya

Authors
  1. A. L. Márquez
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  2. C. Gil
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  3. F. Manzano-Agugliaro
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  4. F. G. Montoya
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  5. A. Fernández
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  6. R. Baños
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Sao Paulo at Sao Carlos, Sao Carlos, SP, Brazil

    Andre Ponce de Leon F. de Carvalho

  2. Department of Computing, Science and Control, Faculty of Science, University of Salamanca, Plaza de la Merced S/N, 37008, Salamanca, Spain

    Sara Rodríguez-González

  3. Department of Computing, Science and Control, Faculty of Science, University of Salamanca, Plaza de la Merced S/N, 37008, Salamanca, Spain

    Juan F. De Paz Santana  & Juan M. Corchado Rodríguez  & 

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Márquez, A.L., Gil, C., Manzano-Agugliaro, F., Montoya, F.G., Fernández, A., Baños, R. (2010). Multi-Objective Evolutionary Algorithms Used in Greenhouse Planning for Recycling Biomass into Energy. In: de Leon F. de Carvalho, A.P., Rodríguez-González, S., De Paz Santana, J.F., Rodríguez, J.M.C. (eds) Distributed Computing and Artificial Intelligence. Advances in Intelligent and Soft Computing, vol 79. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14883-5_60

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  • DOI: https://doi.org/10.1007/978-3-642-14883-5_60

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-14882-8

  • Online ISBN: 978-3-642-14883-5

  • eBook Packages: EngineeringEngineering (R0)

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