Sequence classification is the task of predicting a class label given sequence observations. In many applications such as healthcare monitoring or intrusion detection, early crucial to prompt intervention. this work, we learn classifiers that favour from an evolving observation trace. While state-of-the-art are neural networks, and in particular LSTMs, our take form finite state automata learne...

This work presents a method for optimum design of structures, where the design variables can he considered as Continuous or discrete. The variables are chosen as sizing variables as well as coordinates of joints. The main idea is to reduce the number of structural analyses and the overal cost of optimization. In each design cycle, first the structural response quantities such as forces, displac...

this article presents the application of two algorithms: heuristic big bang-big crunch (hbb-bc) and a heuristic particle swarm ant colony optimization (hpsaco) to discrete optimization of reinforced concrete planar frames subject to combinations of gravity and lateral loads based on aci 318-08 code. the objective function is the total cost of the frame which includes the cost of concrete, formw...

This paper deals with discrete-event simulation based on optimization of a catchment basin management. The integration of optimization techniques into modeling and simulation relies on the evolution of the studied model using decisions based on previous simulation results. Three different categories of optimization via simulationmethods can be found in the literature: rank-and-selection methods...

We develop an algorithmic theory of convex optimization over discrete sets. Using a combination of algebraic and geometric tools we are able to provide polynomial time algorithms for solving broad classes of convex combinatorial optimization problems and convex integer programming problems in variable dimension. We discuss some of the many applications of this theory including to quadratic prog...

An efficient method for size and layout optimization of the truss structures is presented in this paper. In order to this, an efficient method by combining an improved discrete particle swarm optimization (IDPSO) and method of moving asymptotes (MMA) is proposed. In the hybrid of IDPSO and MMA, the nodal coordinates defining the layout of the structure are optimized with MMA, and afterwards the...