Handbook of AI-based Metaheuristics  book cover
1st Edition

Handbook of AI-based Metaheuristics

  • Available for pre-order. Item will ship after September 10, 2021
ISBN 9780367753030
September 10, 2021 Forthcoming by CRC Press
440 Pages 48 Color & 23 B/W Illustrations

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Book Description

At the heart of the optimization domain are mathematical modelling of the problem and the solution methodologies. In recent times, the problems are becoming larger, 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, as well as newly devised metaheuristic algorithms.

The book will be a valuable reference to researchers from industry and academia, as well as Masters and PhD students around the globe working in the metaheuristics and applications domain.

Table of Contents


Section I: Socio-inspired Methods

Brain Storm Optimization Algorithm

Mohammed El-Abd

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, João Luiz Vilar Dias

Marriage in Honey Bees Optimisation in Continuous Domains       

Jing Liu, Sreenatha Anavatti, Matthew Garratt, Hussein A. Abbass

Structural Optimization using Genetic Algorithm     

Ravindra Desai


Section II:Physics and Chemistry-based Methods    


Gravitational Search Algorithm: Theory, Literature Review, and Applications

Amin Hashemi, Mohammad Bagher Dowlatshahi, Hossein Nezamabadi-pou

Stochastic Diffusion Search   

Andrew Owen Martin


Section III: Bio-inspired Methods     


The League Championship Algorithm: Applications and Extensions          

Ali Husseinzadeh Kashan, Alireza Balavand, Somayyeh Karimiyan, Fariba Soleimani

Cultural Algorithm for Optimization 

Carlos Artemio Coello

Application of Teaching-Learning Based Optimization on Solving of Time Cost Optimization Problems 

Vedat Toğan, Tayfun Dede, Hasan Basri Başağa

Social Learning Optimization

Yue-Jiao Gong

Constraint Handling in Multi-Cohort Intelligence Algorithm

Apoorva S Shastri, Anand J Kulkarni


Section IV: Swarm-based Methods   


Bee Colony Optimization and its Applications         

Dušan Teodorović, Tatjana Davidović, Milica Šelmić, Miloš Nikolić

A Bumble Bees Mating Optimization Algorithm for the Location Routing Problem with Stochastic Demands           

Magdalene Marinaki, Yannis Marinakis

A Glowworm Swarm Optimization Algorithm for the Multiobjective Energy Reduction Multi-Depot Vehicle Routing Problem        

Emmanouela Rapanaki, Iraklis-Dimitrios Psychas, Magdalene Marinaki, Yannis Marinakis

Monarch Butterfly Optimization       

Liwen Xie, Gai-Ge Wang

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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)