Modelling history-dependent parameters in the SMPS format for stochastic programming.

This paper proposes two extensions to the SMPS format for stochastic programs to permit modelling of autoregressive-moving average (ARMA) processes. Sampling-based algorithms can thus proceed independently of any underlying modelling system, increasing efficiency. An illustrative example demonstrates the power of the new constructs. [ABSTRACT FROM AUTHOR]