Sinha G. Modern Optimization Methods for Science,Eng..Tech..2020

Textbook in PDF format

This book reviews the fundamentals, background and theoretical concepts of optimization principles in comprehensive manner along with their potentials applications and implementation strategies. The book will be very useful for wide spectrum of target readers such as research scholars, academia, and industry professionals.
Achieving a better solution or improving the performance of existing system design is an ongoing a process for which scientists, engineers, mathematicians and researchers have been striving for many years. Ever increasingly practical and robust methods have been developed, and every new generation of computers with their increased power and speed allows for the development and wider application of new types of solutions. This book defines the fundamentals, background and theoretical concepts of optimization principles in a comprehensive manner along with their potential applications and implementation strategies. It encompasses linear programming, multivariable methods for risk assessment, nonlinear methods, ant colony optimization, particle swarm optimization, multi-criterion and topology optimization, learning classifier, case studies on six sigma, performance measures and evaluation, multi-objective optimization problems, machine learning approaches, genetic algorithms and quality of service optimizations. The book will be very useful for wide spectrum of target readers including students and researchers in academia and industry.
Front matter
Introduction and background to optimization theory
Performance evaluation and measures
Evolutionary techniques in the design of PID controllers
A variational approach to substantial efficiency for linear multi-objective optimization problems with implications for market problems
A machine learning approach for engineering optimization tasks
Simulation of the formation process of spatial fine structures in environmental safety management systems and optimization of the parameters of dispersive devices
Future directions: IoT, robotics and AI based applications
Efficacy of genetic algorithms for computationally intractable problems
A novel approach for QoS optimization in 4G cellular networks
Linear programming
Multivariable optimization methods for risk assessment of the business processes of manufacturing enterprises
Nonlinear optimization methods—overview and future scope
Implementing the traveling salesman problem using a modified ant colony optimization algorithm
Application of a particle swarm optimization technique in a motor imagery classification problem
Multi-criterion and topology optimization using Lie symmetries for differential equations
Learning classifier system
A case study on the implementation of six sigma tools for process improvement