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EOR
2008
200views more  EOR 2008»
13 years 6 months ago
General variable neighborhood search for the continuous optimization
We suggest a new heuristic for solving unconstrained continuous optimization problems. It is based on a generalized version of the variable neighborhood search metaheuristic. Diff...
Nenad Mladenovic, Milan Drazic, Vera Kovacevic-Vuj...
GECCO
2005
Springer
128views Optimization» more  GECCO 2005»
13 years 11 months ago
Hybrid multiobjective genetic algorithm with a new adaptive local search process
This paper is concerned with a specific brand of evolutionary algorithms: Memetic algorithms. A new local search technique with an adaptive neighborhood setting process is introdu...
Salem F. Adra, Ian Griffin, Peter J. Fleming
IWANN
1999
Springer
13 years 10 months ago
Using Temporal Neighborhoods to Adapt Function Approximators in Reinforcement Learning
To avoid the curse of dimensionality, function approximators are used in reinforcement learning to learn value functions for individual states. In order to make better use of comp...
R. Matthew Kretchmar, Charles W. Anderson
FUZZIEEE
2007
IEEE
14 years 17 days ago
Prototype-less Fuzzy Clustering
Abstract—In contrast to standard fuzzy clustering, which optimizes a set of prototypes, one for each cluster, this paper studies fuzzy clustering without prototypes. Starting fro...
Christian Borgelt
GECCO
2004
Springer
125views Optimization» more  GECCO 2004»
13 years 11 months ago
Population-Based Iterated Local Search: Restricting Neighborhood Search by Crossover
Abstract. Iterated local search (ILS) is a powerful meta-heuristic algorithm applied to a large variety of combinatorial optimization problems. Contrary to evolutionary algorithms ...
Dirk Thierens