the hub location decision is a long term investment and any changes in it take considerable time and money. in real situations, some parameters are uncertain hence, deterministic models cannot be more efficient. the ability of two-stage stochastic programming is to make a long-term decision by considering effects of it in short term decisions simultaneously. in the two-stage stochastic programm...

In the realm of scheduling problems, different sources of uncertainty such as probabilistic durations of jobs or stochastic breakdowns of machines can arise. Given this, one highly desirable characteristic of an intelligent schedule is to bring better punctuality with less efficiency-loss because a dominant factor in customer appreciation is punctuality. It is also one of the most intangible to...

The input to the stochastic orienteering problem [13] consists of a budget B and metric (V, d) where each vertex v ∈ V has a job with a deterministic reward and a random processing time (drawn from a known distribution). The processing times are independent across vertices. The goal is to obtain a nonanticipatory policy (originating from a given root vertex) to run jobs at different vertices, t...

We give an overview of the running time analysis of the random divide-and-conquer algorithm FIND or QUICKSELECT. The results concern moments, distribution of FIND’s running time, the limiting distribution, a stochastic bound and the key: a stochastic fixed point equation.

drought is random and nonlinear phenomenon and using linear stochastic models, nonlinear artificial neural network and hybrid models is advantaged for drought forecasting. this paper presents the performances of autoregressive integrated moving average (arima), direct multi-step neural network (dmsnn), recursive multi-step neural network (rmsnn), hybrid stochastic neural network of directive ap...

Multistage stochastic programming is a key technology for making decisions over time in an uncertain environment. One of the promising areas in which this technology is implementable, is medium term planning of electricity production and trading where decision makers are typically faced with uncertain parameters (such as future demands and market prices) that can be described by stochastic proc...

The joint time-frequency analysis (JTFA) is a signal processing technique in which signals are represented in both the time domain and the frequency domain simultaneously. Recently, this analysis technique has become an extremely powerful tool for analyzing nonstationary time series. One basic problem in business-cycle studies is how to deal with nonstationary time series. The market economy is...