Multi-objective programming (MOP) can simultaneously optimize multi-objectives in mathematical programming models, but the optimization of multi-objectives triggers the issue of Pareto solutions and complicates the derived answers. To address these problems, researchers often incorporate the concepts of fuzzy sets and evolutionary algorithms into MOP models.
Focusing on the methodologies and applications of this field, Fuzzy Multiple Objective Decision Making presents mathematical tools for complex decision making. The first part of the book introduces the most popular methods used to calculate the solution of MOP in the field of multiple objective decision making (MODM). The authors describe multi-objective evolutionary algorithms; expand de novo programming to changeable spaces, such as decision and objective spaces; and cover network data envelopment analysis. The second part focuses on various applications, giving readers a practical, in-depth understanding of MODM.
A follow-up to the authors’ Multiple Attribute Decision Making: Methods and Applications, this book guides practitioners in using MODM methods to make effective decisions. It also extends students’ knowledge of the methods and provides researchers with the foundation to publish papers in operations research and management science journals.
Preface
Chapter 1 : Introduction
Part I : Concepts and Theory of Multi-Objective Decision Making
Chapter 2 : Multi-Objective Evolutionary Algorithms
Chapter 3 : Goal Programming
Chapter 4 : Compromise Solution and TOPSIS
Chapter 5 : De Novo Programming and Changeable Parameters
Chapter 6 : Multi-Stage Programming
Chapter 7 : Multi-Level Multi-Objective Programming
Chapter 8 : Data Envelopment Analysis
Part II : Applications of Multi-Objective Decision Making
Chapter 9 : Motivation and Resource Allocation for Strategic Alliances through the De Novo Perspective
Chapter 10 : Choosing Best Alliance Partners and Allocating Optimal Alliance Resources Using Fuzzy Multi-Objective Dummy Programming Model
Chapter 11 : Multiple-Objective Planning for Supply Chain Production and Distribution Model: Bicycle Manufacturer
Chapter 12 : Fuzzy Interdependent Multi-Objective Programming
Chapter 13 : Novel Algorithm for Uncertain Portfolio Selection
Chapter 14 : Multi-Objective Optimal Planning for Designing Relief Delivery Systems
Chapter 15 : Comparative Productivity Efficiency for Global Telecoms
Chapter 16 : Fuzzy Multiple Objective Programming in Interval Piecewise Regression Model
Bibliography
Notes
Index
