Surrogate modeling can overcome computational and data-privacy constraints of micro-scale economic models and support their incorporation into large-scale simulations and interactive simulation experiments. We compare four data-driven methods to reproduce the aggregated crop area response...

We analyze a periodic review stochastic inventory model with T periods and I items. At the beginning of each period, the inventory position of each item can be adjusted by placing an order or by salvaging some of the inventory. There is a limited capacity for the total inventory held at the end...

We provide the first approximation algorithm for dynamic newsvendor networks with stochastic demand and backlogging. Specifically, under a mild cost condition we prove the cost of a base-stock policy is less than 1.618 times the cost of an optimal policy. This answers an open question of Van...

We revisit the simplicial approximation scheme of [43, 44, 45] with a new randomized approach for selecting the grid points of the Bellman function’s piecewise linear approximation in a stochastic dynamic programming model for multireservoir optimization. Unlike the previous approach that...

We introduce a fast upper-envelope scan (FUES) method to compute solutions for dynamic programming problems with continuous and discrete choices. The FUES method builds on the standard endogenous grid method (EGM). Standard EGM applied to problems with continuous and discrete choices does not by...

In today’s complex financial markets, the importance of cash flow management has dramatically increased. In this regard, the present study proposes a multi-objective programming model to configure cash flow management with an inventory control approach. Minimizing the earning quality (the...

In this paper we propose an algorithm for the solution of optimalcontrol problems with nonlinear models based on a generalised Gauss-Newton algorithm but making use of analytic model derivatives. Themethod is implemented in WinSolve, a general nonlinear model solution program

An optimum supply value and the maximum expected profit are hardly affected by the type of demand distribution. The difference between quantities is at most one-tenth of the demand standard deviation in presented numerical examinations for the typical range of margin to discount ratio values. We...

Motivated by the rapid growth of the Cloud Cost Management and Optimization (CCMO) industry to support the exploding cloud-computing market, we study an infinite-horizon, stochastic optimization problem from the viewpoint of a firm that employs cloud resources to process incoming orders (or...

We consider the solution of a recurrent sub–problem within both constrained and unconstrained Nonlinear Programming: namely the minimization of a quadratic function subject to linear constraints. This problem appears in a number of LBM frameworks, and to some extent it reveals a close analogy...