A Flocking-Based Approach for Distributed Stochastic Optimization

Distributed vs. Centralized Particle Swarm Optimization for Learning Flocking Behaviors

In this paper we address the automatic synthesis of controllers for the coordinated movement of multiple mobile robots. We use a noise-resistant version of Particle Swarm Optimization to learn in simulation a set of 50 weights of a plastic artificial neural network. Two learning strategies are applied: homogeneous centralized learning, in which every robot runs the same controller and the perfo...

A Stochastic Optimization Model for Groundwater Management

A Stochastic Optimization Model for Groundwater Management

A duality-based approach for distributed min-max optimization

In this paper we consider a distributed optimization scenario in which a set of processors aims at cooperatively solving a class of min-max optimization problems. This set-up is motivated by peakdemand minimization problems in smart grids. Here, the goal is to minimize the peak value over a finite horizon with: (i) the demand at each time instant being the sum of contributions from different de...

A Distributed Agent-based Approach for Robust Optimization

Structural design and optimization in engineering address increasingly non-standard optimization problems (NSP). These problems are characterized by complex topology conditions of the optimization space (w.r.t. nonlinearity, multimodality, discontinuity etc.). By that, NSP can only be solved by means of computer simulations. Hereby, the corresponding numerical approaches applied often tend to b...