The steel-making and continuous casting system (SCCS) is the bottleneck in the iron and steel production, SCCS often involve various uncertainties such as the emergency customer orders, inaccurate estimate of ingredient components, the unpredictable machine breakdown or the inaccurate estimate of processing time. How to consider such uncertainties to build a better schedule in a limited time by...

A memory control for T-S fuzzy discrete-time systems with sto- chastic input delay is proposed in this paper. Dierent from the common assumptions on the time delay in the existing literatures, it is assumed in this paper that the delays vary randomly and satisfy some probabilistic dis- tribution. A new state space model of the discrete-time T-S fuzzy system is derived by introducing some stocha...

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 renewable energy resources such as wind power have recently attracted more researchers’ attention. it is mainly due to the aggressive energy consumption, high pollution and cost of fossil fuels. in this era, the future fluctuations of these time series should be predicted to increase the reliability of the power network. in this paper, the dynamic characteristics and short-term predictabili...

Stochastic processing networks arise as models in manufacturing, telecommunications, computer systems and the service industry. Common characteristics of these networks are that they have entities, such as jobs, customers or packets, that move along routes, wait in buffers, receive processing from various resources, and are subject to the effects of stochastic variability through such quantitie...

Stochastic processing networks arise as models in manufacturing, telecommunications, transportation, computer systems, the customer service industry and biochemical reaction networks. Common characteristics of these networks are that they have entities, such as jobs, packets, vehicles, customers or molecules, that move along routes, wait in buffers, receive processing from various resources, an...

In the context of public transportation system, improving the service quality and robustness through minimizing the average passengers waiting time is a real challenge. This study provides robust stochastic programming models for train timetabling problem in urban rail transit systems. The objective is minimization of the weighted summation of the expected cost of passenger waiting time, its va...

We show how a technique from signal processing known as zero-delay convolution can be used to develop more efficient dynamic programming algorithms for a broad class of stochastic optimization problems. This class includes several variants of discrete stochastic shortest path, scheduling, and knapsack problems, all of which involve making a series of decisions over time that have stochastic con...