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GECCO
2008
Springer
163views Optimization» more  GECCO 2008»
13 years 6 months ago
Embedded evolutionary multi-objective optimization for worst case robustness
In Multi-Objective Problems (MOPs) involving uncertainty, each solution might be associated with a cluster of performances in the objective space depending on the possible scenari...
Gideon Avigad, Jürgen Branke
GECCO
2009
Springer
145views Optimization» more  GECCO 2009»
13 years 9 months ago
Investigating and exploiting the bias of the weighted hypervolume to articulate user preferences
Optimizing the hypervolume indicator within evolutionary multiobjective optimizers has become popular in the last years. Recently, the indicator has been generalized to the weight...
Anne Auger, Johannes Bader, Dimo Brockhoff, Eckart...
GECCO
2007
Springer
308views Optimization» more  GECCO 2007»
13 years 11 months ago
Multiobjective clustering with automatic k-determination for large-scale data
Web mining - data mining for web data - is a key factor of web technologies. Especially, web behavior mining has attracted a great deal of attention recently. Behavior mining invo...
Nobukazu Matake, Tomoyuki Hiroyasu, Mitsunori Miki...
CEC
2008
IEEE
13 years 11 months ago
Differential evolution for discrete optimization: An experimental study on Combinatorial Auction problems
: Differential evolutionary (DE) mutates solution vectors by the weighted difference of other vectors using arithmetic operations. As these operations cannot be directly extended t...
Jingqiao Zhang, Viswanath Avasarala, Arthur C. San...
GECCO
2007
Springer
300views Optimization» more  GECCO 2007»
13 years 11 months ago
Methodology to select solutions from the pareto-optimal set: a comparative study
The resolution of a Multi-Objective Optimization Problem (MOOP) does not end when the Pareto-optimal set is found. In real problems, a single solution must be selected. Ideally, t...
José C. Ferreira, Carlos M. Fonseca, Ant&oa...