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AAAI
1998
13 years 11 months ago
Highest Utility First Search Across Multiple Levels of Stochastic Design
Manydesign problems are solved using multiple levels of abstraction, wherea design at one level has combinatorially manychildren at the next level. A stochastic optimization metho...
Louis I. Steinberg, J. Storrs Hall, Brian D. Davis...
GECCO
2008
Springer
144views Optimization» more  GECCO 2008»
13 years 11 months ago
Multiobjective robustness for portfolio optimization in volatile environments
Multiobjective methods are ideal for evolving a set of portfolio optimisation solutions that span a range from highreturn/high-risk to low-return/low-risk, and an investor can cho...
Ghada Hassan, Christopher D. Clack
GECCO
2008
Springer
155views Optimization» more  GECCO 2008»
13 years 11 months ago
Modularity and symmetry in computational embryogeny
Modularity and symmetry are two properties observed in almost every engineering and biological structure. The origin of these properties in nature is still unknown. Yet, as engine...
Or Yogev, Andrew A. Shapiro, Erik K. Antonsson
GECCO
2008
Springer
108views Optimization» more  GECCO 2008»
13 years 11 months ago
The effects of mutation and directed intervention crossover when applied to scheduling chemotherapy
This paper discusses the effects of mutation and directed intervention crossover approaches when applied to the derivation of cancer chemotherapy treatment schedules. Unlike trad...
Paul M. Godley, David E. Cairns, Julie Cowie, Kevi...
GECCO
2008
Springer
120views Optimization» more  GECCO 2008»
13 years 11 months ago
A robust evolutionary framework for multi-objective optimization
Evolutionary multi-objective optimization (EMO) methodologies, suggested in the beginning of Nineties, focussed on the task of finding a set of well-converged and well-distribute...
Kalyanmoy Deb