Stochastic Shortest Path problems (SSPs), a subclass of Markov Decision Problems (MDPs), can be efficiently dealt with using Real-Time Dynamic Programming (RTDP). Yet, MDP models are often uncertain (obtained through statistics or guessing). The usual approach is robust planning: searching for the best policy under the worst model. This paper shows how RTDP can be made robust in the common case...

In this paper, a single-product, single-machine system under Markovian deterioration of machine condition and demand uncertainty is studied.  The objective is to find the optimal intervals for inspection and preventive maintenance activities in a condition-based maintenance planning with discrete monitoring framework. At first, a stochastic dynamic programming model whose state variable is the ...

in this paper, global robust stability of stochastic impulsive recurrent neural networks with time-varyingdelays which are represented by the takagi-sugeno (t-s) fuzzy models is considered. a novel linear matrix inequality (lmi)-based stability criterion is obtained by using lyapunov functional theory to guarantee the asymptotic stability of uncertain fuzzy stochastic impulsive recurrent neural...

The dense wavelength division multiplexing routing and provisioning problem with uncertain demands and a fixed budget is modeled as a multicriteria optimization problem. To obtain a robust design for this problem, the primary objective is to minimize a regret function that models the total amount of over and/or under provisioning in the network resulting from uncertainty in a demand forecast. P...

This paper addressed a scheduling problem which handles urgent tasks along with existing schedules. The uncertainties in this come from random process of schedules and unknown upcoming tasks. To deal the uncertainties, proposes stochastic integer programming (SIP) based aggregated online method. method is illustrated through study case outpatient clinic block-wise system under hybrid policy com...

Traditional stochastic inventory models assume full knowledge of the demand distribution. However, in practice, it is often difficult to completely characterize the demand distribution, especially with little or outdated historical data. In these uncertain environments, good inventory management has to be robust, i.e., perform well under most demand scenarios. In this paper, we study the newsve...

In this study, an interval fuzzy-robust two-stage stochastic-robust programming (IFRTSRP) model is developed for water resources management under uncertainty. The developed IFRTSRPmodel incorporates two-stage stochastic programming (TSP), fuzzy robust programming (FRP), interval linear programming (ILP), and stochastic robust optimization (SRO) within a general optimization framework. The IFRTS...

Health service management plays a crucial role in human life. Blood related operations are considered as one of the important components of the health services. This paper presents a bi-objective mixed integer linear programming model for dynamic location-allocation of blood facilities that integrates strategic and tactical decisions. Due to the epistemic uncertain nature of ...

Social responsibility is a key factor that could result in success and achieving great benefits for supply chains. Responsiveness and reliability are important social responsibility measures for consumers and all stakeholders that strategists and company managers should be concerned about them in long-term planning horizon. Although, presence of uncertainties as an intrinsic part of supply chai...