Abstract. In this paper, a new fuzzy logic-based approach to production scheduling in the presence of uncertain disruptions is presented. The approach is applied to a real-life pro...
Abstract. Kernel based methods (such as k-nearest neighbors classifiers) for AI tasks translate the classification problem into a proximity search problem, in a space that is usu...
Abstract. This paper introduces a new algorithm, based on the concept of ejection chains, to effectively target vehicle routing problems with time window constraints (VRPTW). Ejec...
Abstract. The maximum diversity problem (MDP) consists in identifying, in a population, a subset of elements, characterized by a set of attributes, that present the most diverse ch...
L. F. Santos, Marcos Henrique Ribeiro, Alexandre P...
A lot of heuristic approaches have been explored in the last two decades in order to tackle large size optimization problems. These areas include parallel meta-heuristics, hybrid m...
We present a shared memory approach to the parallelization of the Ant Colony Optimization (ACO) metaheuristic and a performance comparison with an existing message passing implemen...
Image registration is a very active research area in computer vision, namely it is used to find a transformation between two images taken under different conditions. Point matchi...
The nature of computer networks and the manner in which network services are provided are changing dramatically. Network architectures that employ virtual mobile agents to provide...
Vishakh, Nicholas Urrea, Tadashi Nakano, Tatsuya S...
Overfitting is a fundamental problem of most machine learning techniques, including genetic programming (GP). Canary functions have been introduced in the literature as a concept ...