Abstract At the early stage of public health emergencies, when conventional medical reserves prepared are insufficient, and productivity could temporarily not meet surge in demand, donations can be used to cover excess demand for supplies a large extent. This paper explicitly considers allocation problem limited during emergency, incorporating uncertainty donated priorities care centers. The is...

Abstract This paper presents a column-and-constraint generation algorithm for two-stage stochastic programming problems. A distinctive feature of the is that it does not assume fixed recourse and as consequence values dimensions matrix can be uncertain. The proposed contains multi-cut (partial) Benders decomposition deterministic equivalent model special cases used to trade-off computational sp...

Computational studies on two-stage stochastic programming problems indicate that aggregate models have better scale-up properties than disaggregate ones, though the threshold of breaking even may be high. In this paper we attempt to explain this phenomenon, and to lower this threshold. We present the on-demand accuracy approach of Oliveira and Sagastizábal in a form which shows that this approa...

The main focus of this paper is in a discussion of complexity of stochastic programming problems. We argue that two-stage (linear) stochastic programming problems with recourse can be solved with a reasonable accuracy by using Monte Carlo sampling techniques, while multi-stage stochastic programs, in general, are intractable. We also discuss complexity of chance constrained problems and multi-s...

Supply chain network design (SCND) problem has recently been gaining attention because an integrated management of the supply chain (SC) can reduce the unexpected/undesirable events and can affect definitely the efficiency of all the chain. A critical component of the planning activities of a manufacturing firm is the efficient design of its SC. Hence, SCND affords a sensitive platform for effi...

Problem statement: The most important character within optimization problem is the uncertainty of the future returns. Approach: To handle such problems, we utilized probabilistic methods alongside with optimization techniques. We developed single stage and two stage stochastic programming with recourse. The models were developed for risk adverse investors and the objective of the stochastic pro...