Meta-Heuristics Optimization Algorithms in Engineering, Business, Economics, and Finance - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Meta-Heuristics Optimization Algorithms in Engineering, Business, Economics, and Finance write by Vasant, Pandian M.. This book was released on 2012-09-30. Meta-Heuristics Optimization Algorithms in Engineering, Business, Economics, and Finance available in PDF, EPUB and Kindle. Optimization techniques have developed into a significant area concerning industrial, economics, business, and financial systems. With the development of engineering and financial systems, modern optimization has played an important role in service-centered operations and as such has attracted more attention to this field. Meta-heuristic hybrid optimization is a newly development mathematical framework based optimization technique. Designed by logicians, engineers, analysts, and many more, this technique aims to study the complexity of algorithms and problems. Meta-Heuristics Optimization Algorithms in Engineering, Business, Economics, and Finance explores the emerging study of meta-heuristics optimization algorithms and methods and their role in innovated real world practical applications. This book is a collection of research on the areas of meta-heuristics optimization algorithms in engineering, business, economics, and finance and aims to be a comprehensive reference for decision makers, managers, engineers, researchers, scientists, financiers, and economists as well as industrialists.
Handbook of Research on Emergent Applications of Optimization Algorithms
Handbook of Research on Emergent Applications of Optimization Algorithms - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Handbook of Research on Emergent Applications of Optimization Algorithms write by Vasant, Pandian. This book was released on 2017-10-31. Handbook of Research on Emergent Applications of Optimization Algorithms available in PDF, EPUB and Kindle. Modern optimization approaches have attracted an increasing number of scientists, decision makers, and researchers. As new issues in this field emerge, different optimization methodologies must be developed and implemented. The Handbook of Research on Emergent Applications of Optimization Algorithms is an authoritative reference source for the latest scholarly research on modern optimization techniques for solving complex problems of global optimization and their applications in economics and engineering. Featuring coverage on a broad range of topics and perspectives such as hybrid systems, non-cooperative games, and cryptography, this publication is ideally designed for students, researchers, and engineers interested in emerging developments in optimization algorithms.
Optimization Using Evolutionary Algorithms and Metaheuristics
Optimization Using Evolutionary Algorithms and Metaheuristics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Optimization Using Evolutionary Algorithms and Metaheuristics write by Kaushik Kumar. This book was released on 2019-08-22. Optimization Using Evolutionary Algorithms and Metaheuristics available in PDF, EPUB and Kindle. 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
Handbook of Research on Modern Optimization Algorithms and Applications in Engineering and Economics
Handbook of Research on Modern Optimization Algorithms and Applications in Engineering and Economics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Handbook of Research on Modern Optimization Algorithms and Applications in Engineering and Economics write by Vasant, Pandian. This book was released on 2016-03-08. Handbook of Research on Modern Optimization Algorithms and Applications in Engineering and Economics available in PDF, EPUB and Kindle. Modern optimization approaches have attracted many research scientists, decision makers and practicing researchers in recent years as powerful intelligent computational techniques for solving several complex real-world problems. The Handbook of Research on Modern Optimization Algorithms and Applications in Engineering and Economics highlights the latest research innovations and applications of algorithms designed for optimization applications within the fields of engineering, IT, and economics. Focusing on a variety of methods and systems as well as practical examples, this book is a significant resource for graduate-level students, decision makers, and researchers in both public and private sectors who are seeking research-based methods for modeling uncertain real-world problems. .
Meta-heuristic and Evolutionary Algorithms for Engineering Optimization
Meta-heuristic and Evolutionary Algorithms for Engineering Optimization - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Meta-heuristic and Evolutionary Algorithms for Engineering Optimization write by Omid Bozorg-Haddad. This book was released on 2017-10-09. Meta-heuristic and Evolutionary Algorithms for Engineering Optimization available in PDF, EPUB and Kindle. A detailed review of a wide range of meta-heuristic and evolutionary algorithms in a systematic manner and how they relate to engineering optimization problems This book introduces the main metaheuristic algorithms and their applications in optimization. It describes 20 leading meta-heuristic and evolutionary algorithms and presents discussions and assessments of their performance in solving optimization problems from several fields of engineering. The book features clear and concise principles and presents detailed descriptions of leading methods such as the pattern search (PS) algorithm, the genetic algorithm (GA), the simulated annealing (SA) algorithm, the Tabu search (TS) algorithm, the ant colony optimization (ACO), and the particle swarm optimization (PSO) technique. Chapter 1 of Meta-heuristic and Evolutionary Algorithms for Engineering Optimization provides an overview of optimization and defines it by presenting examples of optimization problems in different engineering domains. Chapter 2 presents an introduction to meta-heuristic and evolutionary algorithms and links them to engineering problems. Chapters 3 to 22 are each devoted to a separate algorithm— and they each start with a brief literature review of the development of the algorithm, and its applications to engineering problems. The principles, steps, and execution of the algorithms are described in detail, and a pseudo code of the algorithm is presented, which serves as a guideline for coding the algorithm to solve specific applications. This book: Introduces state-of-the-art metaheuristic algorithms and their applications to engineering optimization; Fills a gap in the current literature by compiling and explaining the various meta-heuristic and evolutionary algorithms in a clear and systematic manner; Provides a step-by-step presentation of each algorithm and guidelines for practical implementation and coding of algorithms; Discusses and assesses the performance of metaheuristic algorithms in multiple problems from many fields of engineering; Relates optimization algorithms to engineering problems employing a unifying approach. Meta-heuristic and Evolutionary Algorithms for Engineering Optimization is a reference intended for students, engineers, researchers, and instructors in the fields of industrial engineering, operations research, optimization/mathematics, engineering optimization, and computer science. OMID BOZORG-HADDAD, PhD, is Professor in the Department of Irrigation and Reclamation Engineering at the University of Tehran, Iran. MOHAMMAD SOLGI, M.Sc., is Teacher Assistant for M.Sc. courses at the University of Tehran, Iran. HUGO A. LOÁICIGA, PhD, is Professor in the Department of Geography at the University of California, Santa Barbara, United States of America.
