The problem of production management can often be cast in the form of a linear program with uncertain parameters and risk constraints. Typically, such problems are treated in the framework of multi-stage Stochastic Programming. Recently, a Robust Counterpart (RC) approach has been proposed, in which the decisions are optimized for the worst realizations of problem parameters. However, an applic...

Immediately after a disruption, in order to minimize the negative impact inflicted on society, its imperative re-establish interdicted critical services enabled by infrastructure networks. In this paper, we study stochastic network recovery problem that tackles planning of restoration activities (considering limited resources) links so pre-disruption service flows can be re-established as quick...

This paper considers a robust H¥ state feedback control problem for linear uncertain systems with stochastic uncertainty. The uncertainty class considered in the paper involves uncertain multiplicative white noise perturbations which satisfy a certain variance constraint. A state feedback controller is presented which guarantees a prescribed level of disturbance attenuation for all admissible s...

background and objectives: a sudden jump in blood demand during natural disasters may have strong negative impact on the performance of blood supply chain. appropriate response to the emergency situations, requires predictive approach to determining the optimal allocation of blood supply chain resources for various disaster scenarios. the present study, thus, presents an optimization model aime...

A multi-objective two stage stochastic programming model is proposed to deal with a multiperiodmulti-product multi-site production-distribution planning problem for a midterm planning horizon. The presented model involves majority of supply chain cost parameters such as transportation cost, inventory holding cost, shortage cost, production cost. Moreover some respects as lead time, outsourcing,...

recently, much attention has been given to stochastic demand due to uncertainty in the real -world. in the literature, decision-making models and suppliers' selection do not often consider inventory management as part of shopping problems. on the other hand, the environmental sustainability of a supply chain depends on the shopping strategy of the supply chain members. the supplier selection pl...

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...

This paper introduces a robust inventory routing problem where a supplier distributes a single product to multiple customers facing dynamic uncertain demands over a finite discrete time horizon. The probability distribution of the uncertain demand at each customer is not fully specified. The only available information is that these demands are independent and symmetric random variables which ca...