We give multi-stage stochastic programming formulations for lot-sizing problems where costs, demands and order lead times follow a general discrete-time stochastic process with finite support. We characterize the properties of an optimal solution and give a dynamic programming algorithm, polynomial in input size, when orders do not cross in time.

We consider deployment problems where a mobile robotic network must optimize its configuration in a distributed way in order to minimize a steady-state cost function that depends on the spatial distribution of certain probabilistic events of interest. Three classes of problems are discussed in detail: coverage control problems, spatial partitioning problems, and dynamic vehicle routing problems...

Tracking multiple navigating targets in a bounded region is a common problem that arises in many real-life applications, such as surveillance and reconnaissance. This paper introduces a distributed approach for a well-defined tracking problem, which can be shown to be an NP-hard problem. First, a stochastic target motion model that can be used by agents for dynamic deployment is introduced. Giv...

The present study sustainable management of Guilan Saravan Sylvan Park was planned. The used method in the form of decision support model in three10-year period was studied for parks of various states and with considering the economic, ecological and social criteria during the years 2008 to 2038. By using hierarchical fuzzy analysis method, the reaching to an optimal level of economic, ecologic...

This paper presents the optimization of the location and feedback gains of active bar in a closed loop control system for stochastic piezoelectric smart truss structures under stationary random excitation. The mathematical model with reliability constraints on the mean square value of the structural random dynamic displacement and stress response is developed based on maximization of dissipatio...

Dynamic Bayesian networks (DBNs) are a powerful and exible methodology for representing and computing with probabilistic models of stochastic processes. In the past decade, there has been increasing interest in applying them to practical problems, and this thesis shows that they can be used eeectively in the eld of automatic speech recognition. A principle characteristic of dynamic Bayesian net...

This study presents a dynamic way in a DG planning problem instead of the last static or pseudo-dynamic planning point of views. A new way in modeling the DG units’ output power and the load uncertainties based on the probability rules is proposed in this paper. A sensitivity analysis on the stochastic nature of the electricity price and global fuel price is carried out through a proposed model...

Abstract Mobile Ad-Hoc Networks are currently experiencing a second youth in terms of research interest as well providing benefits to our society. Clearly, this has been fostered by the wide range applications that have become actually feasible thanks pervasive and increasing presence smartphones, drones, sensors other small devices with communication sensing capability. Aiming deploy solutions...