Multi Objective Optimization using Artificial Intelligence Techniques

This book PDF is perfect for those who love Technology & Engineering genre, written by Seyedali Mirjalili and published by Springer which was released on 24 July 2019 with total hardcover pages 58. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Multi Objective Optimization using Artificial Intelligence Techniques books below.

Multi Objective Optimization using Artificial Intelligence Techniques
Author : Seyedali Mirjalili
File Size : 52,7 Mb
Publisher : Springer
Language : English
Release Date : 24 July 2019
ISBN : 9783030248352
Pages : 58 pages
Get Book

Multi Objective Optimization using Artificial Intelligence Techniques by Seyedali Mirjalili Book PDF Summary

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 widely-used algorithms, such as Multi-objective Particle Swarm Optimizer, Multi-Objective Genetic Algorithm and Multi-objective GreyWolf Optimizer Due to the simplicity of the techniques and flexibility, readers from any field of study can employ them for solving multi-objective optimization problem. The book provides the source codes for all the proposed algorithms on a dedicated webpage.

Multi Objective Optimization using Artificial Intelligence Techniques

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 Machine Learning

Recently, increasing interest has been shown in applying the concept of Pareto-optimality to machine learning, particularly inspired by the successful developments in evolutionary multi-objective optimization. It has been shown that the multi-objective approach to machine learning is particularly successful to improve the performance of the traditional single objective machine learning

Get Book
Multi Objective Optimization in Computational Intelligence  Theory and Practice

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
Bio Inspired Systems  Computational and Ambient Intelligence

This book constitutes the refereed proceedings of the 10th International Work-Conference on Artificial Neural Networks, IWANN 2009, held in Salamanca, Spain in June 2009. The 167 revised full papers presented together with 3 invited lectures were carefully reviewed and selected from over 230 submissions. The papers are organized in thematic sections on theoretical foundations and

Get Book
Multi Objective Optimization in Theory and Practice I  Classical Methods

Multi-Objective Optimization in Theory and Practice is a traditional two-part approach to solving multi-objective optimization (MOO) problems namely the use of classical methods and evolutionary algorithms. This first book is devoted to classical methods including the extended simplex method by Zeleny and preference-based techniques. This part covers three main topics

Get Book
Multi Objective Decision Making

Many real-world decision problems have multiple objectives. For example, when choosing a medical treatment plan, we want to maximize the efficacy of the treatment, but also minimize the side effects. These objectives typically conflict, e.g., we can often increase the efficacy of the treatment, but at the cost of

Get Book
Applications Of Multi objective Evolutionary Algorithms

This book presents an extensive variety of multi-objective problems across diverse disciplines, along with statistical solutions using multi-objective evolutionary algorithms (MOEAs). The topics discussed serve to promote a wider understanding as well as the use of MOEAs, the aim being to find good solutions for high-dimensional real-world design applications. The

Get Book
2021 IEEE 4th International Conference on Big Data and Artificial Intelligence  BDAI

2021 IEEE the 4th International Conference on Big Data and Artificial Intelligence (BDAI 2021) will be held at Ocean University of China, Qingdao, China during July 02 04, 2021 The aim of BDAI 2021 is to set up a forum for scholars, researchers & scientists to present their latest research work and results of in related fields

Get Book