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GECCO
2004
Springer
112views Optimization» more  GECCO 2004»
13 years 10 months ago
Some Issues on the Implementation of Local Search in Evolutionary Multiobjective Optimization
This paper discusses the implementation of local search in evolutionary multiobjective optimization (EMO) algorithms for the design of a simple but powerful memetic EMO algorithm. ...
Hisao Ishibuchi, Kaname Narukawa
CEC
2010
IEEE
13 years 3 months ago
A novel hybrid evolutionary strategy and its periodization with multi-objective genetic optimizers
— This work investigates the effects of the periodization of local and global multi-objective search algorithms. To this, we introduce a model for periodization and define a new...
Paul Kaufmann, Tobias Knieper, Marco Platzner
CEC
2008
IEEE
13 years 11 months ago
Solution diversity in multi-objective optimization: A study in virtual reality
— Solution diversity in evolutionary multi-objective optimization is considered. Although the Pareto front is ubiquitously used for the multi-objective optimization, the method o...
Özer Ciftcioglu, Michael S. Bittermann
CEC
2008
IEEE
13 years 11 months ago
An investigation on evolutionary gradient search for multi-objective optimization
—Evolutionary gradient search is a hybrid algorithm that exploits the complementary features of gradient search and evolutionary algorithm to achieve a level of efficiency and r...
Chi Keong Goh, Yew-Soon Ong, Kay Chen Tan, Eu Jin ...
EMO
2006
Springer
124views Optimization» more  EMO 2006»
13 years 8 months ago
I-MODE: An Interactive Multi-objective Optimization and Decision-Making Using Evolutionary Methods
With the popularity of efficient multi-objective evolutionary optimization (EMO) techniques and the need for such problem-solving activities in practice, EMO methodologies and EMO ...
Kalyanmoy Deb, Shamik Chaudhuri