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» Solving Hierarchical Optimization Problems Using MOEAs
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TEC
2008
88views more  TEC 2008»
14 years 9 months ago
A Simulated Annealing-Based Multiobjective Optimization Algorithm: AMOSA
This paper describes a simulated annealing based multiobjective optimization algorithm that incorporates the concept of archive in order to provide a set of tradeoff solutions for ...
Sanghamitra Bandyopadhyay, Sriparna Saha, Ujjwal M...
HAIS
2009
Springer
14 years 7 months ago
A Three-Objective Evolutionary Approach to Generate Mamdani Fuzzy Rule-Based Systems
Abstract. In the last years, several papers have proposed to adopt multiobjective evolutionary algorithms (MOEAs) to generate Mamdani fuzzy rulebased systems with different trade-o...
Michela Antonelli, Pietro Ducange, Beatrice Lazzer...
GECCO
2008
Springer
199views Optimization» more  GECCO 2008»
14 years 10 months ago
Analysis of multi-objective evolutionary algorithms to optimize dynamic data types in embedded systems
New multimedia embedded applications are increasingly dynamic, and rely on Dynamically-allocated Data Types (DDTs) to store their data. The optimization of DDTs for each target em...
José Ignacio Hidalgo, José L. Risco-...
TEC
2002
161views more  TEC 2002»
14 years 9 months ago
A fast and elitist multiobjective genetic algorithm: NSGA-II
Multiobjective evolutionary algorithms (EAs) that use nondominated sorting and sharing have been criticized mainly for their: 1) ( 3) computational complexity (where is the number ...
Kalyanmoy Deb, Samir Agrawal, Amrit Pratap, T. Mey...
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CEC
2007
IEEE
15 years 4 months ago
Improving hypervolume-based multiobjective evolutionary algorithms by using objective reduction methods
— Hypervolume based multiobjective evolutionary algorithms (MOEA) nowadays seem to be the first choice when handling multiobjective optimization problems with many, i.e., at lea...
Dimo Brockhoff, Eckart Zitzler