Author: André A. Keller

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

eBook: US $49 Special Offer (PDF + Printed Copy): US $166
Printed Copy: US $142
Library License: US $196
ISBN: 978-1-68108-569-2 (Print)
ISBN: 978-1-68108-568-5 (Online)
Year of Publication: 2017
DOI: 10.2174/97816810856851170101


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.


André A. Keller
Center for Research in Computer Science
Signal and Automatic Control of Lille
University of Lille – CNRS


.Multi-Objective Optimization In Theory and Practice II: Metaheuristic Algorithms.
.Arduino and SCILAB based Projects.
.Arduino meets MATLAB: Interfacing, Programs and Simulink.
.Budget Optimization and Allocation: An Evolutionary Computing Based Model.