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Author Coello, Carlos A. Coello
Source CiteSeerX
Content type Text
Publisher IEEE Press
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Evolutionary Multiobjective Optimization Technique ♦ Evolutionary Multi-objective Optimization ♦ Multiobjective Optimization ♦ Multiobjective Nature ♦ Promising Area ♦ Updated Survey ♦ Special Session ♦ Peer-reviewed Journal ♦ Important Research Topic ♦ Pioneering Work ♦ Popular Evolutionary Multiobjective Optimization Technique ♦ Genetic-based Search ♦ Technical Paper ♦ Main Application ♦ Future Research ♦ Interest Group ♦ Notable Increment ♦ Multiple Objective ♦ New Area ♦ Future Trend ♦ International Conference ♦ Late 1960s
Description Proceedings of the Congress on Evolutionary Computation
This paper reviews some of the most popular evolutionary multiobjective optimization techniques currently reported in the literature, indicating some of their main applications, their advantages, disadvantages, and degree of aplicability. Finally, some of the most promising areas of future research are briefly discussed. 1 Introduction Since the pioneering work of Rosenberg in the late 1960s regarding the possibility of using genetic-based search to deal with multiple objectives [1], this new area of research (now called Evolutionary Multi-Objective Optimization, or EMOO for short) has grown considerably as indicates the notable increment (mainly in the last 15 years) of technical papers in international conferences and peer-reviewed journals, special sessions in international conferences and interest groups in the Internet 1 . Multiobjective optimization is with no doubt a very important research topic both for scientists and engineers, not only because of the multiobjective nature...
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article
Publisher Date 1999-01-01