We propose an algorithm for function approximation that evolves a set of hierarchical piece-wise linear regressors. The algorithm, named HIRE-Lin, follows the iterative rule learn...
For the p-median problem we study complexity of finding a local minimum in the worst and the average cases. We introduce several neighborhoods and show that the corresponding loca...
Ekaterina Alekseeva, Yury Kochetov, Alexander Plya...
Ant colony optimization (ACO) is a well known metaheuristic. In the literature it has been used for tackling many optimization problems. Often, ACO is hybridized with a local sear...
Neighborhood search heuristics like local search and its variants are some of the most popular approaches to solve discrete optimization problems of moderate to large size. Apart ...
—Reinforcement learning is a framework in which an agent can learn behavior without knowledge on a task or an environment by exploration and exploitation. Striking a balance betw...
Zhengqiao Ji, Q. M. Jonathan Wu, Maher A. Sid-Ahme...