We present a new approach to the design and implementation of probabilistic programming languages (PPLs), based on idea stochastically estimating probability density ratios necessary for inference. By relaxing usual PPL constraint that these densities be computed exactly, we are able eliminate many common restrictions in current PPLs, deliver language that, first time, simultaneously supports f...

We present StochasticPrograms.jl, a user-friendly and powerful open-source framework for stochastic programming written in the Julia language. The includes both modeling tools structure-exploiting optimization algorithms. Stochastic models can be efficiently formulated using an expressive syntax, instantiated, inspected, analyzed interactively. scales seamlessly to distributed environments. Sma...

performance evaluation of electricity distribution units is an important issue between researchers and regulators. classic data envelopment analysis models with deterministic data have been used by many authors to measure efficiency of power distribution units in different countries. however, data envelopment analysis with stochastic data are rarely used to measure efficiency of distribution co...

Stochastic Approach to Vehicle Routing Problem: Development and Theories Abstract In this article, a chance constrained (CCP) formulation of the Vehicle Routing Problem (VRP) is proposed. The reality is that once we convert some special form of probabilistic constraint into their equivalent deterministic form then a nonlinear constraint generates. Knowing that reliable computer software...

We consider an asset-liability management (ALM) problem for a defined benefit pension fund (PF). The PF manager is assumed to follow a maximal fund valuation problem facing an extended set of risk factors:  due to the longevity of the    PF members, the inflation affecting salaries in real terms and future incomes, interest rates and market factors affecting jointly the PF liability and asset p...