Reference
S. S. Farahani, T. van den Boom, and B. De
Schutter, "On optimization of stochastic max-min-plus-scaling systems - An
approximation approach,"
Automatica, vol. 83, pp.
20-27, Sept. 2017.
Abstract
A large class of discrete-event and hybrid systems can be described by a
max-min-plus-scaling (MMPS) model, i.e., a model in which the main operations
are maximization, minimization, addition, and scalar multiplication.
Accordingly, optimization of MMPS systems appears in different problems defined
for discrete-event and hybrid systems. For a stochastic MMPS system, this
optimization problem is computationally highly demanding as often numerical
integration has to be used to compute the objective function. The aim of this
paper is to decrease such computational complexity by applying an approximation
method that is based on the moments of a random variable and that can be
computed analytically.
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BibTeX
@article{Farvan:17-004,
author = {Farahani, Samira S. and van den Boom, Ton and De Schutter, Bart},
title = {On Optimization of Stochastic Max-Min-Plus-Scaling Systems --
{An} Approximation Approach},
journal = {Automatica},
volume = {83},
pages = {20--27},
month = sep,
year = {2017}
}