ABSTRACT

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 M

chapter 1|16 pages

- Introduction

chapter 2|8 pages

- Multi-Objective Evolutionary Algorithms

chapter 3|12 pages

- Goal Programming

chapter 4|10 pages

- Compromise Solution and TOPSIS

chapter 6|10 pages

- Multi-Stage Programming

chapter 7|8 pages

- Multi-Level Multi-Objective Programming

chapter 8|18 pages

- Data Envelopment Analysis