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GECCO
2006
Springer
132views Optimization» more  GECCO 2006»
15 years 8 months ago
Combining genetic algorithms with squeaky-wheel optimization
The AI optimization algorithm called "Squeaky-Wheel Optimization" (SWO) has proven very effective in a variety of real-world applications. Although the ideas behind SWO ...
Justin Terada, Hoa Vo, David Joslin
GECCO
2000
Springer
120views Optimization» more  GECCO 2000»
15 years 8 months ago
An Improved Adaptive Multi-Start Approach to Finding Near-Optimal Solutions to the Euclidean TSP
We present an "adaptive multi-start" genetic algorithm for the Euclidean traveling salesman problem that uses a population of tours locally optimized by the Lin-Kernigha...
Dan Bonachea, Eugene Ingerman, Joshua Levy, Scott ...
AIPS
2007
15 years 6 months ago
Monitoring Plan Optimality During Execution
A great deal of research has addressed the problem of generating optimal plans, but these plans are of limited use in circumstances where noisy sensors, unanticipated exogenous ac...
Christian Fritz, Sheila A. McIlraith
AIPS
2008
15 years 6 months ago
The Complexity of Optimal Planning and a More Efficient Method for Finding Solutions
We present a faster method of solving optimal planning problems and show that our solution performs up to an order of magnitude faster than Satplan on a variety of problems from t...
Katrina Ray, Matthew L. Ginsberg
WSC
2007
15 years 6 months ago
Stochastic trust region gradient-free method (strong): a new response-surface-based algorithm in simulation optimization
Response Surface Methodology (RSM) is a metamodelbased optimization method. Its strategy is to explore small subregions of the parameter space in succession instead of attempting ...
Kuo-Hao Chang, L. Jeff Hong, Hong Wan