1st Edition

Handbook of AI-based Metaheuristics

Edited By Anand J. Kulkarni, Patrick Siarry Copyright 2022
    418 Pages 48 Color & 23 B/W Illustrations
    by CRC Press

    418 Pages 48 Color & 23 B/W Illustrations
    by CRC Press

    At the heart of the optimization domain are mathematical modeling of the problem and the solution methodologies. The problems are becoming larger and with growing complexity. Such problems are becoming cumbersome when handled by traditional optimization methods. This has motivated researchers to resort to artificial intelligence (AI)-based, nature-inspired solution methodologies or algorithms.

    The Handbook of AI-based Metaheuristics provides a wide-ranging reference to the theoretical and mathematical formulations of metaheuristics, including bio-inspired, swarm-based, socio-cultural, and physics-based methods or algorithms; their testing and validation, along with detailed illustrative solutions and applications; and newly devised metaheuristic algorithms.

    This will be a valuable reference for researchers in industry and academia, as well as for all Master’s and PhD students working in the metaheuristics and applications domains.


    Section I Bio-Inspired Methods

    Chapter 1 Brain Storm Optimization Algorithm

    Marwa Sharawi, Mohammadreza Gholami,

    and Mohammed El-Abd

    Chapter 2 Fish School Search: Account for the First Decade

    Carmelo José Abanez Bastos-Filho, Fernando Buarque de Lima-Neto,

    Anthony José da Cunha Carneiro Lins, Marcelo Gomes Pereira de

    Lacerda, Mariana Gomes da Motta Macedo, Clodomir Joaquim de

    Santana Junior, Hugo Valadares Siqueira, Rodrigo Cesar Lira da Silva,

    Hugo Amorim Neto, Breno Augusto de Melo Menezes, Isabela Maria

    Carneiro Albuquerque, João Batista Monteiro Filho, Murilo Rebelo Pontes,

    and João Luiz Vilar Dias

    Chapter 3 Marriage in Honey Bees Optimization in Continuous Domains

    Jing Liu, Sreenatha Anavatti, Matthew Garratt,

    and Hussein A. Abbass

    Chapter 4 Structural Optimization Using Genetic Algorithm...

    Ravindra Desai

    Section II Physics and Chemistry-Based Methods

    Chapter 5 Gravitational Search Algorithm: Theory, Literature Review,

    and Applications

    Amin Hashemi, Mohammad Bagher Dowlatshahi,

    and Hossein Nezamabadi-pour

    Chapter 6 Stochastic Diffusion Search

    Andrew Owen Martin

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    Section III Socio-inspired Methods

    Chapter 7 The League Championship Algorithm: Applications and Extensions

    Ali Husseinzadeh Kashan, Alireza Balavand, Somayyeh Karimiyan,

    and Fariba Soleimani

    Chapter 8 Cultural Algorithms for Optimization

    Carlos Artemio Coello Coello and Ma Guadalupe Castillo Tapia

    Chapter 9 Application of Teaching-Learning-Based Optimization

    on Solving of Time Cost Optimization Problems

    Vedat Toğan, Tayfun Dede, and Hasan Basri Başağa

    Chapter 10 Social Learning Optimization

    Yue-Jiao Gong

    Chapter 11 Constraint Handling in Multi-Cohort Intelligence Algorithm

    Apoorva S. Shastri and Anand J. Kulkarni

    Section IV Swarm-Based Methods

    Chapter 12 Bee Colony Optimization and Its Applications

    Dušan Teodorović, Tatjana Davidović, Milica Šelmić,

    and Miloš Nikolić

    Chapter 13 A Bumble Bees Mating Optimization Algorithm for the Location

    Routing Problem with Stochastic Demands

    Magdalene Marinaki and Yannis Marinakis

    Chapter 14 A Glowworm Swarm Optimization Algorithm for the Multi-Objective

    Energy Reduction Multi-Depot Vehicle Routing Problem

    Emmanouela Rapanaki, Iraklis-Dimitrios Psychas,

    Magdalene Marinaki, and Yannis Marinakis

    Chapter 15 Monarch Butterfly Optimization

    Liwen Xie and Gai-Ge Wang


    Patrick Siarry is a Professor of Automatics and Informatics at the University of Paris-Est Créteil, where he leads the Image and Signal Processing team in the Laboratoire Images, Signaux et Systèmes Intelligents (LiSSi).

    Anand J Kulkarni is Associate Professor at the Symbiosis Center for Research and Innovation, Symbiosis International (Deemed University).