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GECCO
2005
Springer
154views Optimization» more  GECCO 2005»
15 years 8 months ago
Genetic algorithms using low-discrepancy sequences
The random number generator is one of the important components of evolutionary algorithms (EAs). Therefore, when we try to solve function optimization problems using EAs, we must ...
Shuhei Kimura, Koki Matsumura
EVOW
2007
Springer
15 years 9 months ago
Tackling the Container Loading Problem: A Hybrid Approach Based on Integer Linear Programming and Genetic Algorithms
Abstract. This paper presents a novel hybrid approach for solving the Container Loading (CL) problem based on the combination of Integer Linear Programming (ILP) and Genetic Algori...
Napoleão Nepomuceno, Plácido Rog&eac...
GECCO
2010
Springer
153views Optimization» more  GECCO 2010»
15 years 6 months ago
Multi-task evolutionary shaping without pre-specified representations
Shaping functions can be used in multi-task reinforcement learning (RL) to incorporate knowledge from previously experienced tasks to speed up learning on a new task. So far, rese...
Matthijs Snel, Shimon Whiteson
SYNTHESE
2008
84views more  SYNTHESE 2008»
15 years 3 months ago
How experimental algorithmics can benefit from Mayo's extensions to Neyman-Pearson theory of testing
Although theoretical results for several algorithms in many application domains were presented during the last decades, not all algorithms can be analyzed fully theoretically. Exp...
Thomas Bartz-Beielstein
IJSYSC
2000
74views more  IJSYSC 2000»
15 years 3 months ago
Towards the evolutionary emergence of increasingly complex advantageous behaviours
The generation of complex entities with advantageous behaviours beyond our manual design capability requires long-term incremental evolution with continuing emergence. In this pap...
A. D. Channon, Robert I. Damper