Soft computing techniques for engineering optimization /

This book covers the issues related to optimization of engineering and management problems using soft computing techniques with an industrial outlook. It covers a broad area related to real life complex decision making problems using a heuristics approach. It also explores a wide perspective and fut...

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Bibliographic Details
Main Authors:	Kumar, K. (Kaushik), 1968- (Author), Roy, Supriyo (Author), Davim, J. Paulo (Author)
Corporate Author:	Taylor & Francis
Format:	eBook
Language:	English
Published:	Boca Raton, FL : CRC Press/Taylor and Francis Group, [2019].
Series:	Science, technology, and management series.
Subjects:	Soft computing. Industrial engineering. Mathematical optimization. Informatique douce. Génie industriel. Optimisation mathématique. industrial engineering. MATHEMATICS > Arithmetic. TECHNOLOGY > Electricity. TECHNOLOGY > Manufacturing. Industrial engineering Mathematical optimization Soft computing Electronic books.
Online Access:	Connect to the full text of this electronic book

Table of Contents:

Chapter 1. Introduction to Optimization & Relevance of Soft Computing Techniques Towards Optimal Solution. Section 1: Optimization. 2. Various Soft Computing Techniques and their Description. Section 2: History of Heuristics / Search Algorithms. 3. Single Objective Optimization using Response Surface Methodology. 4. Multi Objective Optimization using Weighted Principal Component Analysis. 5. Single Objective Optimization using Taguchi Technique (Maximization). 6. Single Objective Optimization using Taguchi Technique (Minimization). 7. Multi-Objective Optimization using Grey-Taguchi Technique. 8. Single Objective Optimization using Taguchi Coupled Fuzzy Logic. 9. Multi-Objective Optimization using Non-Dominated Sorting Genetic Algorithm. 10. Single Objective Optimization using Artificial Bee Colony Algorithm. Section 3: Working with MINITAB and MATLAB. 11. Working with MINITAB for Optimization using Taguchi Technique. 12. Working with MATLAB for Optimization using Artificial Neural Network. 13. Working with MATLAB for Optimization using Genetic Algorithm.