We describe a two-stage robust optimization approach for solving network flow and design problems with uncertain demand. In two-stage network optimization, one defers a subset of the flow decisions until after the realization of the uncertain demand. Availability of such a recourse action allows one to come up with less conservative solutions compared to singlestage optimization. However, this ...

The hub location–allocation problem under uncertainty is a real-world task arising in the areas such as public and freight transportation and telecommunication systems. In many applications, the demand is considered as inexact because of the forecasting inaccuracies or human’s unpredictability. This study addresses the robust uncapacitated multiple allocation hub location problem with a set of ...

Traditional approaches in inventory control first estimate the demand distribution among a predefined family of distributions based on data fitting of historical demand observations, and then optimize the inventory control using the estimated distributions. These approaches often lead to fragile solutions whenever the preselected family of distributions was inadequate. In this work we propose a...

a linear programming model has been presented for finding an appropriate planning in order to maximize hotel revenue. in this model, a special planning horizon has been considered that includes several busy days of a year. there are several reservation periods that may start a few months earlier. each period of reservation may have different prices and so result different incomes. hotel custome...

Many supply chain problems involve optimization of various conflicting objectives. This paper formulates a green supply chain network throughout a two-stage mixed integer linear problem with uncertain demand and stochastic environmental respects level. The first objective function of the proposed model considers minimization of supply chain costs while the second objective function minimizes CO...

In this paper, impacts of various uncertainties such as random outages of generating units and transmission lines, forecasting errors of load demand and wind power, in the presence of Demand response (DR) programs on power generation scheduling are studied. The problem is modelled in the form of a two-stage stochastic unit commitment (UC) which by solving it, the optimal solutions of UC as well...

In this paper, a dynamical supply networks model with stochastic switched topology is presented, in which the stochastic switched topology is dependent on a continuous time Markov process. The goal is to design the state-feedback control strategies to stabilize the dynamical supply networks. Based on Lyapunov stability theory, sufficient conditions for the existence of state feedback control st...

Moment robust optimization models formulate a stochastic problem with an uncertain probability distribution of parameters described by its moments. In this paper we study a two-stage stochastic convex programming model using moments to define the probability ambiguity set for the objective function coefficients in both stages. A decomposition based algorithm is given. We show that this two-stag...

This article explores the development of previous models to determine hubs in a competitive environment. In this paper, by comparing parameters of the ticket price, travel time and the service quality of hub airports, airline hubs are divided into six categories. The degree of importance of travel time and travel cost are determined by a multivariate Lagrange interpolation method, which can pla...