Skip to main content
Have a personal or library account? Click to login
Multi-Objective Optimization in Theory and Practice I: Classical Methods Cover

Multi-Objective Optimization in Theory and Practice I: Classical Methods

Publisher:Bentham Science
By: Andre A Keller  
Paid access
|Dec 2017
Product purchase options
Description
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 through nine chapters. The first topic focuses on the design of such MOO problems their complexities including nonlinearities and uncertainties and optimality theory. The second topic introduces the founding solving methods including the extended simplex method to linear MOO problems and weighting objective methods. The third topic deals with particular structures of MOO problems such as mixed-integer programming hierarchical programming fuzzy logic programming and bimatrix games.

Multi-Objective Optimization in Theory and Practice is a user-friendly book with detailed illustrated calculations examples test functions and small-size applications in Mathematica® (among other mathematical packages) and from scholarly literature. It is an essential handbook for students and teachers involved in advanced optimization courses in engineering information science and mathematics degree programs.
PDF ISBN: 978-1-68108-568-5
Publisher: Bentham Science
Copyright owner: © 2017 Bentham Science Publishers
Publication date: 2017
Language: English
Pages: 300
Related subjects:
Mathematics,
General mathematics

People also read

Multi-Objective Optimization In Theory and Practice II: Metaheuristic Algorithms
Book

Multi-Objective Optimization In Theory and Practice II: Metaheuristic Algorithms

Andre A Keller
Optimization Using Linear Programming
Book

Optimization Using Linear Programming

A. J. Metei, Veena Jain
Optimality Conditions in Vector Optimization
Book

Optimality Conditions in Vector Optimization

Manuel Arana Jimenez, Gabriel Ruiz Garzon, Antonio Rufian Lizana
Optimization Techniques for Decision-making and Information Security
Book

Optimization Techniques for Decision-making and Information Security

Vinod Kumar, Mandeep Mittal, Adesh Kumari
Applied Linear Algebra and Optimization Using MATLAB
Book

Applied Linear Algebra and Optimization Using MATLAB

Rizwan Butt
How to Design Optimization Algorithms by Applying Natural Behavioral Patterns
Book

How to Design Optimization Algorithms by Applying Natural Behavioral Patterns

Rohollah Omidvar, Behrouz Minaei Bidgoli
Fundamentals of Computational Methods for Engineers
Book

Fundamentals of Computational Methods for Engineers

Masud Rana, Wei Xu, Youguang Guo
Budget Optimization and Allocation: An Evolutionary Computing Based Model
Book

Budget Optimization and Allocation: An Evolutionary Computing Based Model

Sudip Kumar Sahana, Moumita Khowas, Keshav Sinha
Engineering Mathematics
Book

Engineering Mathematics

Ramakanta Meher
Multivariable and Vector Calculus
Book

Multivariable and Vector Calculus

David A. Santos, Sarhan M. Musa