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A New Bio-inspired Optimization Algorithm Based on the Self-defense Mechanism of Plants in Nature

  • Book
  • © 2019

Overview

Authors:
  1. Camilo Caraveo

    1. Division of Graduate Studies, Tijuana Institute of Technology, Tijuana, Mexico

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  2. Fevrier Valdez

    1. Division of Graduate Studies, Tijuana Institute of Technology, Tijuana, Mexico

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  3. Oscar Castillo

    1. Division of Graduate Studies, Tijuana Institute of Technology, Tijuana, Mexico

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  • Presents a new meta-heuristic optimization algorithm, inspired by plant self-defense mechanisms in nature
  • Based on the predator–prey mathematical model by Lotka and Volterra
  • Written by experts in the field

Part of the book series: SpringerBriefs in Applied Sciences and Technology (BRIEFSAPPLSCIENCES)

Part of the book sub series: SpringerBriefs in Computational Intelligence (BRIEFSINTELL)

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Table of contents (7 chapters)

  1. Front Matter

    Pages i-viii
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  2. Introduction

    • Camilo Caraveo, Fevrier Valdez, Oscar Castillo
    Pages 1-4

  3. Theory and Background

    • Camilo Caraveo, Fevrier Valdez, Oscar Castillo
    Pages 5-7

  4. Self-defense of the Plants

    • Camilo Caraveo, Fevrier Valdez, Oscar Castillo
    Pages 9-12

  5. Predator-Prey Model

    • Camilo Caraveo, Fevrier Valdez, Oscar Castillo
    Pages 13-15

  6. Proposed Method

    • Camilo Caraveo, Fevrier Valdez, Oscar Castillo
    Pages 17-22

  7. Case Studies

    • Camilo Caraveo, Fevrier Valdez, Oscar Castillo
    Pages 23-52

  8. Conclusions

    • Camilo Caraveo, Fevrier Valdez, Oscar Castillo
    Pages 53-54

  9. Back Matter

    Pages 55-57
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Keywords

About this book

This book presents a new meta-heuristic algorithm, inspired by the self-defense mechanisms of plants in nature. Numerous published works have demonstrated the various self-defense mechanisms (survival strategies) plants use to protect themselves against predatory organisms, such as herbivorous insects. The proposed algorithm is based on the predator–prey mathematical model originally proposed by Lotka and Volterra, consisting of two nonlinear first-order differential equations, which allow the growth of two interacting populations (prey and predator) to be modeled. The proposed meta-heuristic is able to produce excellent results in several sets of benchmark optimization problems. Further, fuzzy logic is used for dynamic parameter adaptation in the algorithm.

Authors and Affiliations

  • Division of Graduate Studies, Tijuana Institute of Technology, Tijuana, Mexico

    Camilo Caraveo, Fevrier Valdez, Oscar Castillo

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