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An Evaluation of a Metaheuristic Artificial Immune System for Household Energy Optimization

Author

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  • Maria Navarro-Caceres
  • Pramod Herath
  • Gabriel Villarrubia
  • Francisco Prieto-Castrillo
  • G. Kumar Venyagamoorthy

Abstract

Devices in a smart home should be connected in an optimal way; this helps save energy and money. Among numerous optimization models that can be found in the literature, we would like to highlight artificial immune systems, which use special bioinspired algorithms to solve optimization problems effectively. The aim of this work is to present the application of an artificial immune system in the context of different energy optimization problems. Likewise, a case study is performed in which an artificial immune system is incorporated in order to solve an energy management problem in a domestic environment. A thorough analysis of the different strategies is carried out to demonstrate the ability of an artificial immune system to find a successful optima which satisfies the problem constraints.

Suggested Citation

  • Maria Navarro-Caceres & Pramod Herath & Gabriel Villarrubia & Francisco Prieto-Castrillo & G. Kumar Venyagamoorthy, 2018. "An Evaluation of a Metaheuristic Artificial Immune System for Household Energy Optimization," Complexity, Hindawi, vol. 2018, pages 1-11, July.
    • Handle: RePEc:hin:complx:9597158
    DOI: 10.1155/2018/9597158
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    Cited by:

    1. Fatima Ezzahra Achamrah & Fouad Riane & Evren Sahin & Sabine Limbourg, 2022. "An Artificial-Immune-System-Based Algorithm Enhanced with Deep Reinforcement Learning for Solving Returnable Transport Item Problems," Sustainability, MDPI, vol. 14(10), pages 1-29, May.

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