In this paper, we propose a simple and flexible execution model that (i) supports a wide spectrum of alternative optimization and execution strategies and their mixtures, (ii) pro...
Yijian Bai, Hetal Thakkar, Haixun Wang, Carlo Zani...
This paper presents a direct reinforcement learning algorithm, called Finite-Element Reinforcement Learning, in the continuous case, i.e. continuous state-space and time. The eval...
Our problem of interest consists of minimizing a separable, convex and differentiable function over a convex set, defined by bounds on the variables and an explicit constraint des...
Continuous GRASP (C-GRASP) is a stochastic local search metaheuristic for finding cost-efficient solutions to continuous global optimization problems subject to box constraints (Hi...
Michael J. Hirsch, Panos M. Pardalos, Mauricio G. ...
Abstract. In 1965 Motzkin and Straus established a remarkable connection between the local/global maximizers of the Lagrangian of a graph G over the standard simplex ∆ and the ma...