RaBVIt-SG, an algorithm for solving Feedback Nash equilibria in Multiplayers Stochastic Differential Games

In a previous work, we have introduced an algorithm, called RaBVItG, used for computing Feedback Nash equilibria of deterministic multiplayers Differential Games. This algorithm is based on a sequence of Game Iterations (i.e., a numerical method to simulate an equilibrium of a Differential Game), combined with Value Iterations (i.e, a numerical method to solve a … Read more

RaBVItG:An Algorithm for Solving a Class of Multi-Players Feedback Nash Differential Games

In this work, we introduce a novel numerical algorithm, called RaBVItG (Radial Basis Value Iteration Game) to approximate feedback-Nash equilibria for deterministic differential games. More precisely, RaBVItG is an algorithm based on value iteration schemes in a meshfree context. It is used to approximate optimal feedback Nash policies for multi-players, trying to tackle the dimensionality … Read more

High-Performance Computing for the Optimization of High-Pressure Thermal treatments in Food Industry

In Food Industry, the combined treatments based on high-pressure and temperature (HPT) are frequently used to increment the durability of the products without damaging their good properties. However, achieving a reasonable compromise between conservation and quality is usually a challenging task. In a previous work, we proposed a decision tool which solves a multi-objective optimization … Read more

A Decision Tool based on a Multi-Objective Methodology for designing High-Pressure Thermal Treatments in Food Industry

In this work, we propose a methodology for designing High-Pressure Thermal processes for food treatment. This approach is based on a multi-objective preference-based evolutionary optimization algorithm, called WASF-GA, combined with a decision strategy which provides the food engineer with the best treatment in accordance with some quality requirements. The resulting method is compared to a … Read more

A Multi-Layer Line Search Method to Improve the Initialization of Optimization Algorithms

We introduce a novel metaheuristic methodology to improve the initialization of a given deterministic or stochastic optimization algorithm. Our objective is to improve the performance of the considered algorithm, called core optimization algorithm, by reducing its number of cost function evaluations, by increasing its success rate and by boosting the precision of its results. In … Read more

Stochastic Topology Design Optimization for Continuous Elastic Materials

In this paper, we develop a stochastic model for topology optimization. We find robust structures that minimize the compliance for a given main load having a stochastic behavior. We propose a model that takes into account the expected value of the compliance and its variance. We show that, similarly to the case of truss structures, … Read more