El-Ghazali Talbi – författare

This book provides a complete background on metaheuristics and shows readers how to design and implement efficient algorithms to solve complex optimization problems across a diverse range of applications, from networking and bioinformatics to engineering design, routing, and scheduling. It presents the main design questions for all families of metaheuristics and clearly illustrates how to implement the algorithms under a software framework to reuse both the design and code.

Throughout the book, the key search components of metaheuristics are considered as a toolbox for:

Designing efficient metaheuristics for multi-objective optimization problems

Designing hybrid, parallel, and distributed metaheuristics

Implementing metaheuristics on sequential and parallel machines

Using many case studies and treating design and implementation independently, this book gives readers the skills necessary to solve large-scale optimization problems quickly and efficiently. It is a valuable reference for practicing engineers and researchers from diverse areas dealing with optimization or machine learning; and graduate students in computer science, operations research, control, engineering, business and management, and applied mathematics.

This book is a new contribution aiming to give some last research findings in the field of optimization and computing. This work is in the same field target than our two previous books published: “Recent Developments in Metaheuristics” and “Metaheuristics for Production Systems”, books in Springer Series in Operations Research/Computer Science Interfaces.

The challenge with this work is to gather the main contribution in three fields, optimization technique for production decision, general development for optimization and computing method and wider spread applications. 

The number of researches dealing with decision maker tool and optimization method grows very quickly these last years and in a large number of fields. We may be able to read nice and worthy works from research developed in chemical, mechanical, computing, automotive and many other fields.

This book presents novel and original metaheuristics developed to solve the cost-balanced traveling salesman problem. This problem was taken into account for the Metaheuristics Competition proposed in MESS 2018, Metaheuristics Summer School, and the top 4 methodologies ranked are included in the book, together with a brief introduction to the traveling salesman problem and all its variants.

The book is aimed particularly at all researchers in metaheuristics and combinatorial optimization areas. 

Key uses are metaheuristics; complex problem solving; combinatorial optimization; traveling salesman problem.

This book constitutes the refereed proceedings of the 9th International Conference on Metaheuristics and Nature Inspired Computing, META 2023, held in Marrakech, Morocco, during November 1-4, 2023. 

The 19 full papers presented in this volume were carefully reviewed and selected from 42 submissions. The papers are divided into the following topical sections: combinatorial optimization; scheduling; continuous optimization; automatic metaheuristics tuning; optimization and machine learning; and applications.

This book constitutes the refereed proceedings of the 7th International Conference on Optimization and Learning, OLA 2024, held in Dubrovnik, Croatia, during May 13–15, 2024.

The 24 full papers presented here were carefully reviewed and selected from 64 submissions. They were organized in the following topical sections: synergies between optimization and machine learning; enhancing optimization and learning techniques; transportation and routing; and applications.