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» On Using Populations of Sets in Multiobjective Optimization
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GECCO
2008
Springer
153views Optimization» more  GECCO 2008»
14 years 10 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...
EMO
2001
Springer
125views Optimization» more  EMO 2001»
15 years 1 months ago
Adapting Weighted Aggregation for Multiobjective Evolution Strategies
The conventional weighted aggregation method is extended to realize multi-objective optimization. The basic idea is that systematically changing the weights during evolution will l...
Yaochu Jin, Tatsuya Okabe, Bernhard Sendhoff
EVOW
2006
Springer
15 years 1 months ago
Optimal Broadcasting in Metropolitan MANETs Using Multiobjective Scatter Search
Mobile Ad-hoc Networks (MANETs) are composed of a set of communicating devices which are able to spontaneously interconnect without any pre-existing infrastructure. In such scenari...
Francisco Luna, Antonio J. Nebro, Bernabé D...
GECCO
2008
Springer
148views Optimization» more  GECCO 2008»
14 years 10 months ago
Accelerating convergence using rough sets theory for multi-objective optimization problems
We propose the use of rough sets theory to improve the first approximation provided by a multi-objective evolutionary algorithm and retain the nondominated solutions using a new ...
Luis V. Santana-Quintero, Carlos A. Coello Coello
91
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GECCO
2007
Springer
156views Optimization» more  GECCO 2007»
15 years 3 months ago
Techniques for highly multiobjective optimisation: some nondominated points are better than others
The research area of evolutionary multiobjective optimization (EMO) is reaching better understandings of the properties and capabilities of EMO algorithms, and accumulating much e...
David W. Corne, Joshua D. Knowles