Model- and simulation-designers are often interested not in the optimum output of their system, but in understanding how the output is sensitive to different parameters. This can...
Sean Luke, Deepankar Sharma, Gabriel Catalin Balan
In this paper, we propose a new approach that consists of the extended compact genetic algorithm (ECGA) and split-ondemand (SoD), an adaptive discretization technique, to economic...
The problem of production and delivery lot-sizing and scheduling of set of items in a two-echelon supply chain over a finite planning horizon is addressed in this paper. A single ...
In this paper we propose a genetic programming approach to learning stochastic models with unsymmetrical noise distributions. Most learning algorithms try to learn from noisy data...
Abstract. This article presents a comprehensive study of different ensemble pruning techniques applied to a bagging ensemble composed of decision stumps. Six different ensemble p...