Robust Optimization is a rapidly developing methodology for handling optimization problems affected by non-stochastic “uncertain-butbounded” data perturbations. In this paper, we overview several selected topics in this popular area, specifically, (1) recent extensions of the basic concept of robust counterpart of an optimization problem with uncertain data, (2) tractability of robust counterpa...

We study a cement transportation problem with asset-management (equipment selection) for strategic planning scenarios involving multiple forms of transportation and network expansion. A deterministic mixed integer programming approach is difficult due to the underlying capacitated multi-commodity network flow model and the need to consider a time-space network to ensure operational feasibility....

Abstract. In this paper we study distributionally robust stochastic programming in a setting 7 where there is a specified reference probability measure and the uncertainty set of probability mea8 sures consists of measures in some sense close to the reference measure. We discuss law invariance of 9 the associated worst case functional and consider two basic constructions of such uncertainty set...

Since third-party logistics (3PL) offers discounted prices for booking containers in advance, the container decisions are preferably made prior to realization of customer demand by companies with international trade business. When facing uncertain influenced various factors, it is significant make proper and order fulfillment plans minimize total cost, including cost penalty an unfulfilled orde...

This study addresses the production planning problem for perishable products, in which the cost and shortage of products are minimized subject to a set of constraints such as warehouse space, labor working time and machine time. Using the concept of postponement, the production process for perishable products is differentiated into two phases to better utilize the resources. A two-stage stochas...

Quantitative optimization techniques have proven to be a powerful tool in tackling complicated decision-making problems in various application domains. Scheduling workforces, pricing airline tickets, managing production systems and designing engineering projects are just a small sample of the myriad industrial applications that have benefited from optimization techniques such as linear, nonline...

The aim of this paper is to propose a robust reliable bi-objective supply chain network design (SCND) model that is capable of controlling different kinds of uncertainties, concurrently. In this regard, stochastic bi-level scenario based programming approach which is used to model various scenarios related to strike of disruptions. The well-known method helps to overcome adverse effects of disr...

In this paper we rst discuss the robust stability of uncertain linear stochastic diierential delay equations. We then extend the theory to cope with the robust stability of uncertain semi-linear stochastic diierential delay equations. We shall also give several examples to illustrate our theory.