Piecewise linear convex functions arise as integrands in stochastic programs. They are Lipschitz continuous on their domain, but do not belong to tensor product Sobolev spaces. Motivated by applying Quasi-Monte Carlo methods we show that all terms of their ANOVA decomposition, except the one of highest order, are smooth if the underlying densities are smooth and a certain geometric condition is...

In this paper we consider stochastic programming problems where the objective function is given as an expected value of a convex piecewise linear random function. With an optimal solution of such a problem we associate a condition number which characterizes well or ill conditioning of the problem. Using theory of Large Deviations we show that the sample size needed to calculate the optimal solu...

Network flow problems with non-convex piecewise linear cost structures arise in many application areas, most notably in freight transportation and supply chain management. In the present paper, we consider mixed-integer programming (MIP) formulations of a generic multi-commodity network flow problem with piecewise linear costs. The formulations we study are based on variable disaggregation tech...

‎‎in this article‎, ‎a new method is introduced to give approximate solution to van der pol equation‎. ‎the proposed method is based on the combination of two different methods‎, ‎the spectral adomian decomposition method (sadm) and piecewise method‎, ‎called the piecewise adomian decomposition method (psadm)‎. ‎the numerical results obtained from the proposed method show that this method is an...

A function on R with multiple local minima is approximated from below, via linear programming, by a linear combination of convex kernel functions using sample points from the given function. The resulting convex kernel underestimator is then minimized, using either a linear equation solver for a linear-quadratic kernel or by a Newton method for a Gaussian kernel, to obtain an approximation to a...

Production optimization of gas-lifted oil fields under facility, routing, and pressure constraints has attracted the attention of researchers and practitioners for its scientific challenges and economic impact. The available methods fall into one of two categories: nonlinear or piecewise-linear approaches. The nonlinear methods optimize simulation models directly or use surrogates obtained by c...