<p>Metaheuristic optimization is a higher-level procedure or heuristic designed to find, generate, or select a heuristic (partial search algorithm) that may provide a sufficiently good solution to an optimization problem, especially with incomplete or imperfect information or limited computation cap
Optimization Using Evolutionary Algorithms and Metaheuristics-Applications in Engineering
โ Scribed by Kaushik Kumar (Editor); J. Paulo Davim (Editor)
- Publisher
- CRC Press
- Year
- 2019
- Leaves
- 149
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
Metaheuristic optimization is a higher-level procedure or heuristic designed to find, generate, or select a heuristic (partial search algorithm) that may provide a sufficiently good solution to an optimization problem, especially with incomplete or imperfect information or limited computation capacity. This is usually applied when two or more objectives are to be optimized simultaneously.
This book is presented with two major objectives. Firstly, it features chapters by eminent researchers in the field providing the readers about the current status of the subject. Secondly, algorithm-based optimization or advanced optimization techniques, which are applied to mostly non-engineering problems, are applied to engineering problems. This book will also serve as an aid to both research and industry. Usage of these methodologies would enable the improvement in engineering and manufacturing technology and support an organization in this era of low product life cycle.
Features:
- Covers the application of recent and new algorithms
- Focuses on the development aspects such as including surrogate modeling, parallelization, game theory, and hybridization
- Presents the advances of engineering applications for both single-objective and multi-objective optimization problems
- Offers recent developments from a variety of engineering fields
- Discusses Optimization using Evolutionary Algorithms and Metaheuristics applications in engineering
โฆ Table of Contents
Part I: Optimization. 1. Foundations and Principles. 2. Neural Networks. 3. Fuzzy Systems. 4. Evolutionary Computation. 5. Rough Sets. Part II: Applications of Optimization. 6. Mechanical Engineering. 7. Power Control and Optimization. 8. Nanoscience and Nanoengineering. 9. Mining Engineering. 10. Signal Processing. 11. Civil Engineering. 12. Optical Engineering. 13. Bioinformatics and Biomedical Engineering. 14. Ecology and Environmental Engineering.
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<div>This book discusses the application of metaheuristic algorithms in a number of important optimization problems in civil engineering. Advances in civil engineering technologies require greater accuracy, efficiency and speed in terms of the analysis and design of the corresponding systems. As suc
The book presents recently developed efficient metaheuristic optimization algorithms and their applications for solving various optimization problems in civil engineering. The concepts can also be used for optimizing problems in mechanical and electrical engineering.ย
<p>The book presents recently developed efficient metaheuristic optimization algorithms and their applications for solving various optimization problems in civil engineering. The concepts can also be used for optimizing problems in mechanical and electrical engineering. </p>
<p><p>This book addresses the principles and applications of metaheuristic approaches in engineering and related fields. The first part covers metaheuristics tools and techniques such as ant colony optimization and Tabu search, and their applications to several classes of optimization problems. In t