Multi Objective Optimization in Computational Intelligence Theory and Practice

This book PDF is perfect for those who love Technology & Engineering genre, written by Thu Bui, Lam and published by IGI Global which was released on 31 May 2008 with total hardcover pages 496. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Multi Objective Optimization in Computational Intelligence Theory and Practice books below.

Multi Objective Optimization in Computational Intelligence Theory and Practice
Multi Objective Optimization in Computational Intelligence Theory and Practice
Author : Thu Bui, Lam
File Size : 50,5 Mb
Publisher : IGI Global
Language : English
Release Date : 31 May 2008
ISBN : 9781599045009
Pages : 496 pages
Get Book

Multi Objective Optimization in Computational Intelligence Theory and Practice by Thu Bui, Lam Book PDF Summary

Multi-objective optimization (MO) is a fast-developing field in computational intelligence research. Giving decision makers more options to choose from using some post-analysis preference information, there are a number of competitive MO techniques with an increasingly large number of MO real-world applications. Multi-Objective Optimization in Computational Intelligence: Theory and Practice explores the theoretical, as well as empirical, performance of MOs on a wide range of optimization issues including combinatorial, real-valued, dynamic, and noisy problems. This book provides scholars, academics, and practitioners with a fundamental, comprehensive collection of research on multi-objective optimization techniques, applications, and practices.

Multi Objective Optimization in Computational Intelligence Theory and Practice

Multi Objective Optimization in Computational Intelligence Theory and Practice by Thu Bui, Lam,Alam, Sameer

Multi-objective optimization (MO) is a fast-developing field in computational intelligence research. Giving decision makers more options to choose from using some post-analysis preference information, there are a number of competitive MO techniques with an increasingly large number of MO real-world applications. Multi-Objective Optimization in Computational Intelligence: Theory and Practice explores

Get Book
Computational Intelligence in Optimization

Computational Intelligence in Optimization by Yoel Tenne,Chi-Keong Goh

This collection of recent studies spans a range of computational intelligence applications, emphasizing their application to challenging real-world problems. Covers Intelligent agent-based algorithms, Hybrid intelligent systems, Machine learning and more.

Get Book
Multi Objective Optimization in Theory and Practice II Metaheuristic Algorithms

Multi Objective Optimization in Theory and Practice II Metaheuristic Algorithms by André A. Keller

Multi-Objective Optimization in Theory and Practice is a simplified two-part approach to multi-objective optimization (MOO) problems. This second part focuses on the use of metaheuristic algorithms in more challenging practical cases. The book includes ten chapters that cover several advanced MOO techniques. These include the determination of Pareto-optimal sets of

Get Book
Computational Intelligence in Expensive Optimization Problems

Computational Intelligence in Expensive Optimization Problems by Yoel Tenne,Chi-Keong Goh

In modern science and engineering, laboratory experiments are replaced by high fidelity and computationally expensive simulations. Using such simulations reduces costs and shortens development times but introduces new challenges to design optimization process. Examples of such challenges include limited computational resource for simulation runs, complicated response surface of the simulation

Get Book
Multi Objective Optimization using Artificial Intelligence Techniques

Multi Objective Optimization using Artificial Intelligence Techniques by Seyedali Mirjalili,Jin Song Dong

This book focuses on the most well-regarded and recent nature-inspired algorithms capable of solving optimization problems with multiple objectives. Firstly, it provides preliminaries and essential definitions in multi-objective problems and different paradigms to solve them. It then presents an in-depth explanations of the theory, literature review, and applications of several

Get Book
Multi Objective Memetic Algorithms

Multi Objective Memetic Algorithms by Chi-Keong Goh,Yew Soon Ong,Kay Chen Tan

The application of sophisticated evolutionary computing approaches for solving complex problems with multiple conflicting objectives in science and engineering have increased steadily in the recent years. Within this growing trend, Memetic algorithms are, perhaps, one of the most successful stories, having demonstrated better efficacy in dealing with multi-objective problems as

Get Book
Sequential Approximate Multiobjective Optimization Using Computational Intelligence

Sequential Approximate Multiobjective Optimization Using Computational Intelligence by Hirotaka Nakayama,Yeboon Yun,Min Yoon

Many kinds of practical problems such as engineering design, industrial m- agement and ?nancial investment have multiple objectives con?icting with eachother. Thoseproblemscanbeformulatedasmultiobjectiveoptimization. In multiobjective optimization, there does not necessarily a unique solution which minimizes (or maximizes) all objective functions. We usually face to the situation in which if we

Get Book
High Performance Simulation Based Optimization

High Performance Simulation Based Optimization by Thomas Bartz-Beielstein,Bogdan Filipič,Peter Korošec,El-Ghazali Talbi

This book presents the state of the art in designing high-performance algorithms that combine simulation and optimization in order to solve complex optimization problems in science and industry, problems that involve time-consuming simulations and expensive multi-objective function evaluations. As traditional optimization approaches are not applicable per se, combinations of computational

Get Book