1 Basic Concepts

All things have already been said, but no one listens, so we always need to start again to talk about the words already said.

---Andre Gide (a famous French writer)

1.1 Introduction

Multi-objective issues have emerged as a natural fad in many disciplines, and their solutions have long been a challenge for researchers. Although Operation Research and other disciplines propose a number of ways to solve this problem, they are too complex and require a different approach.

The use of evolutionary algorithms (EA) To solve this problem has been vigorously promoted, precisely because the evolutionary algorithm is based on the nature of the population, so that a single operation can obtain Pareto optimal solution set of several elements. In addition, the complexity of some multiobjective optimization problems (such as large search space, uncertainty, noise, discontinuity of pereto curve, etc.) makes the traditional multi-objective optimization problem solving method of operational research not very well applied.

1 Basic Concepts