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GECCO
2007
Springer
149views Optimization» more  GECCO 2007»
15 years 10 months ago
Informative performance metrics for dynamic optimisation problems
Existing metrics for dynamic optimisation are designed primarily to rate an algorithm’s overall performance. These metrics show whether one algorithm is better than another, but...
Stefan Bird, Xiaodong Li
EC
2000
187views ECommerce» more  EC 2000»
15 years 4 months ago
Comparison of Multiobjective Evolutionary Algorithms: Empirical Results
In this paper, we provide a systematic comparison of various evolutionary approaches to multiobjective optimization using six carefully chosen test functions. Each test function i...
Eckart Zitzler, Kalyanmoy Deb, Lothar Thiele
GECCO
2005
Springer
131views Optimization» more  GECCO 2005»
15 years 10 months ago
EA models and population fixed-points versus mutation rates for functions of unitation
Using a dynamic systems model for the Simple Genetic Algorithm due to Vose[1], we analyze the fixed point behavior of the model without crossover applied to functions of unitation...
J. Neal Richter, John Paxton, Alden H. Wright
ANOR
2007
165views more  ANOR 2007»
15 years 4 months ago
Financial scenario generation for stochastic multi-stage decision processes as facility location problems
The quality of multi-stage stochastic optimization models as they appear in asset liability management, energy planning, transportation, supply chain management, and other applicat...
Ronald Hochreiter, Georg Ch. Pflug
GECCO
2006
Springer
162views Optimization» more  GECCO 2006»
15 years 8 months ago
Evolutionary learning with kernels: a generic solution for large margin problems
In this paper we embed evolutionary computation into statistical learning theory. First, we outline the connection between large margin optimization and statistical learning and s...
Ingo Mierswa