A New Definition and Calculation Model for Evolutionary Multi-Objective Optimization  

作　　者：Zhou Ai-min, Kang Li-shan, Chen Yu-ping, Huang Yu-zhenState Key Laboratory of Software Engineering, Wuhan University, Wuhan 430072, Hubei, China 

出　　处：《Wuhan University Journal of Natural Sciences》2003年第S1期189-194,共6页武汉大学学报（自然科学英文版）

基　　金：Supported by the National Natural Science Foundation of China(70071042,60073043,60133010)

摘　　要：We present a new definition (Evolving Solutions) for Multi-objective Optimization Problem (MOP) to answer the basic question (what's multi-objective optimal solution?) and advance an asynchronous evolutionary model (MINT Model) to solve MOPs. The new theory is based on our understanding of the natural evolution and the analysis of the difference between natural evolution and MOP, thus it is not only different from the Converting Optimization but also different from Pareto Optimization. Some tests prove that our new theory may conquer disadvantages of the upper two methods to some extent.We present a new definition (Evolving Solutions) for Multi-objective Optimization Problem (MOP) to answer the basic question (what's multi-objective optimal solution?) and advance an asynchronous evolutionary model (MINT Model) to solve MOPs. The new theory is based on our understanding of the natural evolution and the analysis of the difference between natural evolution and MOP, thus it is not only different from the Converting Optimization but also different from Pareto Optimization. Some tests prove that our new theory may conquer disadvantages of the upper two methods to some extent.

关 键 词：evolving equilibrium evolving solutions MINT model multi-objective optimization 

分 类 号：O224[理学—运筹学与控制论]