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GECCO
2005
Springer
182views Optimization» more  GECCO 2005»
14 years 1 months ago
Improving EAX with restricted 2-opt
Edge Assembly Crossover (EAX) is by far the most successful crossover operator in solving the traveling salesman problem (TSP) with Genetic Algorithms (GAs). Various improvements ...
Chen-hsiung Chan, Sheng-An Lee, Cheng-Yan Kao, Hua...
GECCO
2008
Springer
120views Optimization» more  GECCO 2008»
13 years 8 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
GECCO
2005
Springer
103views Optimization» more  GECCO 2005»
14 years 1 months ago
Pricing the 'free lunch' of meta-evolution
A number of recent studies introduced meta-evolutionary strategies and successfully used them for solving problems in genetic programming. While individual results indicate possib...
Alexei V. Samsonovich, Kenneth A. De Jong
PEWASUN
2004
ACM
14 years 1 months ago
A routing protocol for power constrained networks with asymmetric links
In many instances, an ad hoc network consists of nodes with different hardware and software capabilities as well as power limitations. This is the case of ad hoc grids where devi...
Guoqiang Wang, Yongchang Ji, Dan C. Marinescu, Dam...
GECCO
2011
Springer
276views Optimization» more  GECCO 2011»
12 years 11 months ago
Evolution of reward functions for reinforcement learning
The reward functions that drive reinforcement learning systems are generally derived directly from the descriptions of the problems that the systems are being used to solve. In so...
Scott Niekum, Lee Spector, Andrew G. Barto