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Metaheuristics
A unified view of metaheuristics 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 (e.g. local search, tabu search, simulated annealing, e...
Metaheuristics for Bi-level Optimization
This book provides a complete background on metaheuristics to solve complex bi-level optimization problems (continuous/discrete, mono-objective/multi-objective) in a diverse range of application domains. Readers learn to solve large scale bi-level optimization problems by efficiently combining metaheuristics with complementary metaheuristics and mathematical programming approaches. Numerous real-world examples of problems demonstrate how metaheuristics are applied in such fields as networks, logistics and transportation, engineering design, finance and security.
Hybrid Metaheuristics
The main goal of this book is to provide a state of the art of hybrid metaheuristics. The book provides a complete background that enables readers to design and implement hybrid metaheuristics to solve complex optimization problems (continuous/discrete, mono-objective/multi-objective, optimization under uncertainty) in a diverse range of application domains. Readers learn to solve large scale problems quickly and efficiently combining metaheuristics with complementary metaheuristics, mathematical programming, constraint programming and machine learning. Numerous real-world examples of problems and solutions demonstrate how hybrid metaheuristics are applied in such fields as networks, logistics and transportation, bio-medical, engineering design, scheduling.
Metaheuristics for Medicine and Biology
This book highlights recent research on metaheuristics for biomedical engineering, addressing both theoretical and applications aspects. Given the multidisciplinary nature of bio-medical image analysis, it has now become one of the most central topics in computer science, computer engineering and electrical and electronic engineering, and attracted the interest of many researchers. To deal with these problems, many traditional and recent methods, algorithms and techniques have been proposed. Among them, metaheuristics is the most common choice. This book provides essential content for senior and young researchers interested in methodologies for implementing metaheuristics to help solve biomedical engineering problems.
Metaheuristics for Combinatorial Optimization
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.
Optimization and Learning
This volume constitutes the refereed proceedings of the Third International Conference on Optimization and Learning, OLA 2020, held in Cádiz, Spain, in February 2020. The 23 full papers were carefully reviewed and selected from 55 submissions. The papers presented in the volume focus on the future challenges of optimization and learning methods, identifying and exploiting their synergies,and analyzing their applications in different fields, such as health, industry 4.0, games, logistics, etc.
Heuristics for Optimization and Learning
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.
Advances in Multi-Objective Nature Inspired Computing
The purpose of this book is to collect contributions that deal with the use of nature inspired metaheuristics for solving multi-objective combinatorial optimization problems. Such a collection intends to provide an overview of the state-of-the-art developments in this field, with the aim of motivating more researchers in operations research, engineering, and computer science, to do research in this area. As such, this book is expected to become a valuable reference for those wishing to do research on the use of nature inspired metaheuristics for solving multi-objective combinatorial optimization problems.
Metaheuristics and Nature Inspired Computing
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.
Grid Computing for Bioinformatics and Computational Biology
The only single, up-to-date source for Grid issues in bioinformatics and biology Bioinformatics is fast emerging as an important discipline for academic research and industrial applications, creating a need for the use of Grid computing techniques for large-scale distributed applications. This book successfully presents Grid algorithms and their real-world applications, provides details on modern and ongoing research, and explores software frameworks that integrate bioinformatics and computational biology. Additional coverage includes: * Bio-ontology and data mining * Data visualization * DNA assembly, clustering, and mapping * Molecular evolution and phylogeny * Gene expression and micro-ar...
