Population genetics, epidemics, competition, and predation are just some of the biological topics to which stochastic models can be applied. The National Institute for Mathematical and Biological ...

Stochastic programming can effectively describe many decision-making problems in uncertain environments. Unfortunately, such programs are often computationally demanding to solve. In addition, their ...

Although stochastic programming is probably the most effective framework for handling decision problems that involve uncertain variables, it is always a costly task to formulate the stochastic model ...

Dynamic stochastic matching problems arise in a variety of recent applications, ranging from ridesharing and online video games to kidney exchange. Such problems are naturally formulated as Markov ...