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

• Κύριοι συγγραφείς: Caraveo, Camilo (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut), Valdez, Fevrier (http://id.loc.gov/vocabulary/relators/aut), Castillo, Oscar (http://id.loc.gov/vocabulary/relators/aut)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2019.
• Έκδοση: 1st ed. 2019.
• Σειρά: SpringerBriefs in Computational Intelligence,
• Θέματα: Computational intelligence.; Artificial intelligence.; Plant science.; Botany.; Mathematical optimization.; Computational Intelligence.; Artificial Intelligence.; Plant Sciences.; Optimization.
• Φυσική περιγραφή: VIII, 57 p. online resource.
• ISBN: 9783030055516
• ISSN: 2625-3704
• DOI: 10.1007/978-3-030-05551-6

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.