Optimisation under uncertainty has always been a focal point within the Process Systems Engineering (PSE) research agenda. In particular, efficient manipulation of large amount data for uncertain parameters constitutes crucial condition effectively tackling stochastic programming problems. this context, work proposes new data-driven Mixed-Integer Linear Programming (MILP) model Distribution & M...

In this paper, a comprehensive mathematical model for designing an electric power supply chain network via considering preventive maintenance under risk of network failures is proposed. The risk of capacity disruption of the distribution network is handled via using a two-stage stochastic programming as a framework for modeling the optimization problem. An applied method of planning for the net...

Stochastic integer programming is more complicated than stochastic linear programming, as will be explained for the case of the two-stage stochastic programming model. A survey of the results accomplished in this recent field of research is given.

This document shows how to model two-stage stochastic linear programming problems in a GAMS environment. We will demonstrate using a small example, how GAMS can be used to formulate and solve this model as a large LP or using specialized stochastic solvers such as OSL-SE and DECIS. Finally a tailored implementation of the Benders Decomposition algorithm written in GAMS is used to solve the model.

The purpose of the paper is to present existing and discuss modified optimization models and solution techniques which are suitable for engineering decision-making problems containing random elements with emphasis on two decision stages. The developed approach is called two-stage stochastic programming and the paper links motivation, applicability, theoretical remarks, transformations, input da...

introduction: in the present study, dealing with water deficit challenges for gorgan river basin has been considered. golestan province's economy is dependent on agriculture but the occurrence of drought periods reduced the agricultural production and consequently the region's economy is in crisis. therefore, performing studies for programming and management of the water resources of the provin...

background one of most important operations research problems is nurse scheduling problem (nsp) that tries to find an optimal way to assign nurses to shifts with a set of hard constraints. most of the researches are dealing with this problem in deterministic environment with constant parameters. while in the real world applications of nsp, the stochastic nature of some parameters like number of...