Describes how evolutionary algorithms (EAs) can be used to identify, model, and minimize day-to-day problems that arise for researchers in optimization and mobile networkingMobile ad hoc networks (MANETs), vehicular networks (VANETs), sensor networks (SNs), and hybrid networks—each of these require a designer’s keen sense and knowledge of evolutionary algorithms in order to help with the common issues that plague professionals involved in optimization and mobile networking.This book introduces readers to both mobile ad hoc networks and evolutionary algorithms, presenting basic concepts as well as detailed descriptions of each. It demonstrates how metaheuristics and evolutionary algorithms (EAs) can be used to help provide low-cost operations in the optimization process—allowing designers to put some “intelligence” or sophistication into the design. It also offers efficient and accurate information on dissemination algorithms, topology management, and mobility models to address challenges in the field.Evolutionary Algorithms for Mobile Ad Hoc Networks: Instructs on how to identify, model, and optimize solutions to problems that arise in daily researchPresents complete and up-to-date surveys on topics like network and mobility simulatorsProvides sample problems along with solutions/descriptions used to solve each, with performance comparisonsCovers current, relevant issues in mobile networks, like energy use, broadcasting performance, device mobility, and moreEvolutionary Algorithms for Mobile Ad Hoc Networks is an ideal book for researchers and students involved in mobile networks, optimization, advanced search techniques, and multi-objective optimization.

This volume constitutes selected papers presented during the 8th International Conference on Metaheuristics and Nature Inspired Computing, META 2021, held in Marrakech, Morocco, in October 201. Due to the COVID-19 pandemic the conference was partiqally held online. The 16 papers were thoroughly reviewed and selected from the 53 submissions. They are organized in the topical sections on ​combinatorial optimization; continuous optimization; optimization and machine learning; applications.

This volume constitutes selected papers presented during the 8th International Conference on Metaheuristics and Nature Inspired Computing, META 2021, held in Marrakech, Morocco, in October 201. Due to the COVID-19 pandemic the conference was partiqally held online. The 16 papers were thoroughly reviewed and selected from the 53 submissions. They are organized in the topical sections on ​combinatorial optimization; continuous optimization; optimization and machine learning; applications. 

This book constitutes the refereed proceedings of the 6th International Conference on Optimization and Learning, OLA 2023, held in Malaga, Spain, during May 3–5, 2023. The 32 full papers included in this book were carefully reviewed and selected from 78 submissions. They were organized in topical sections as follows: advanced optimization; learning; learning methods to enhance optimization tools; optimization applied to learning methods; and real-world applications.

This book constitutes the refereed proceedings of the 6th International Conference on Optimization and Learning, OLA 2023, held in Malaga, Spain, during May 3–5, 2023. The 32 full papers included in this book were carefully reviewed and selected from 78 submissions. They were organized in topical sections as follows: advanced optimization; learning; learning methods to enhance optimization tools; optimization applied to learning methods; and real-world applications.

Describes how evolutionary algorithms (EAs) can be used to identify, model, and minimize day-to-day problems that arise for researchers in optimization and mobile networkingMobile ad hoc networks (MANETs), vehicular networks (VANETs), sensor networks (SNs), and hybrid networks—each of these require a designer’s keen sense and knowledge of evolutionary algorithms in order to help with the common issues that plague professionals involved in optimization and mobile networking.This book introduces readers to both mobile ad hoc networks and evolutionary algorithms, presenting basic concepts as well as detailed descriptions of each. It demonstrates how metaheuristics and evolutionary algorithms (EAs) can be used to help provide low-cost operations in the optimization process—allowing designers to put some “intelligence” or sophistication into the design. It also offers efficient and accurate information on dissemination algorithms, topology management, and mobility models to address challenges in the field.Evolutionary Algorithms for Mobile Ad Hoc Networks: Instructs on how to identify, model, and optimize solutions to problems that arise in daily researchPresents complete and up-to-date surveys on topics like network and mobility simulatorsProvides sample problems along with solutions/descriptions used to solve each, with performance comparisonsCovers current, relevant issues in mobile networks, like energy use, broadcasting performance, device mobility, and moreEvolutionary Algorithms for Mobile Ad Hoc Networks is an ideal book for researchers and students involved in mobile networks, optimization, advanced search techniques, and multi-objective optimization.

This volume constitutes selected papers presented during the 8th International Conference on Metaheuristics and Nature Inspired Computing, META 2021, held in Marrakech, Morocco, in October 201. Due to the COVID-19 pandemic the conference was partiqally held online. The 16 papers were thoroughly reviewed and selected from the 53 submissions. They are organized in the topical sections on ​combinatorial optimization; continuous optimization; optimization and machine learning; applications.

This volume constitutes selected papers presented during the 8th International Conference on Metaheuristics and Nature Inspired Computing, META 2021, held in Marrakech, Morocco, in October 201. Due to the COVID-19 pandemic the conference was partiqally held online. The 16 papers were thoroughly reviewed and selected from the 53 submissions. They are organized in the topical sections on ​combinatorial optimization; continuous optimization; optimization and machine learning; applications. 

This book constitutes the refereed proceedings of the 6th International Conference on Optimization and Learning, OLA 2023, held in Malaga, Spain, during May 3–5, 2023. The 32 full papers included in this book were carefully reviewed and selected from 78 submissions. They were organized in topical sections as follows: advanced optimization; learning; learning methods to enhance optimization tools; optimization applied to learning methods; and real-world applications.

This book constitutes the refereed proceedings of the 6th International Conference on Optimization and Learning, OLA 2023, held in Malaga, Spain, during May 3–5, 2023. The 32 full papers included in this book were carefully reviewed and selected from 78 submissions. They were organized in topical sections as follows: advanced optimization; learning; learning methods to enhance optimization tools; optimization applied to learning methods; and real-world applications.