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GECCO
2008
Springer
153views Optimization» more  GECCO 2008»
13 years 6 months ago
G-Metric: an M-ary quality indicator for the evaluation of non-dominated sets
An open problem in multiobjective optimization using the Pareto optimality criteria, is how to evaluate the performance of different evolutionary algorithms that solve multi– o...
Giovanni Lizárraga Lizárraga, Arturo...
EC
2002
180views ECommerce» more  EC 2002»
13 years 5 months ago
Combining Convergence and Diversity in Evolutionary Multiobjective Optimization
Over the past few years, the research on evolutionary algorithms has demonstrated their niche in solving multiobjective optimization problems, where the goal is to nd a number of ...
Marco Laumanns, Lothar Thiele, Kalyanmoy Deb, Ecka...
TEC
2002
128views more  TEC 2002»
13 years 4 months ago
A framework for evolutionary optimization with approximate fitness functions
It is not unusual that an approximate model is needed for fitness evaluation in evolutionary computation. In this case, the convergence properties of the evolutionary algorithm are...
Yaochu Jin, Markus Olhofer, Bernhard Sendhoff
FOCI
2007
IEEE
13 years 11 months ago
On the Convergence of Immune Algorithms
Immune Algorithms have been used widely and successfully in many computational intelligence areas including optimization. Given the large number of variants of each operator of thi...
Vincenzo Cutello, Giuseppe Nicosia, Mario Romeo, P...
GECCO
2006
Springer
130views Optimization» more  GECCO 2006»
13 years 9 months ago
An efficient multi-objective evolutionary algorithm with steady-state replacement model
The generic Multi-objective Evolutionary Algorithm (MOEA) aims to produce Pareto-front approximations with good convergence and diversity property. To achieve convergence, most mu...
Dipti Srinivasan, Lily Rachmawati