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104
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CEC
2007
IEEE
15 years 9 months ago
How well do multi-objective evolutionary algorithms scale to large problems
Abstract— In spite of large amount of research work in multiobjective evolutionary algorithms, most have evaluated their algorithms on problems with only two to four objectives. ...
Kata Praditwong, Xin Yao
111
Voted
APPROX
2007
Springer
115views Algorithms» more  APPROX 2007»
15 years 8 months ago
Improved Approximation Algorithms for the Spanning Star Forest Problem
A star graph is a tree of diameter at most two. A star forest is a graph that consists of node-disjoint star graphs. In the spanning star forest problem, given an unweighted graph ...
Ning Chen, Roee Engelberg, C. Thach Nguyen, Prasad...
ISICA
2007
Springer
15 years 8 months ago
A New Evolutionary Decision Theory for Many-Objective Optimization Problems
In this paper the authors point out that the Pareto Optimality is unfair, unreasonable and imperfect for Many-objective Optimization Problems (MOPs) underlying the hypothesis that ...
Zhuo Kang, Lishan Kang, Xiufen Zou, Minzhong Liu, ...
ATAL
2005
Springer
15 years 8 months ago
Impact of problem centralization in distributed constraint optimization algorithms
Recent progress in Distributed Constraint Optimization Problems (DCOP) has led to a range of algorithms now available which differ in their amount of problem centralization. Probl...
John Davin, Pragnesh Jay Modi
GECCO
2008
Springer
148views Optimization» more  GECCO 2008»
15 years 3 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