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Part III: RISK-SENSITIVE COST MODELS
In this part we consider robust production
plans with risk sensitive cost criteria. This consideration is motivated
by the following observations. First, since most manufacturing systems
are large and complex, it is difficult to establish accurate mathematical
models to describe these systems. Modeling errors are inevitable. Second,
in practice, an optimal policy for a subdivision of a big corporation is
usually not an optimal policy for the whole corporation. Optimal solutions
with the usual cost criteria may not be desirable in many real situations.
An alternative approach is to consider robust controls. In some manufacturing
systems, it is more desirable to consider controls that are robust enough
to attenuate uncertain disturbances, such as modeling errors, and therefore
achieve the system stability. Robust control design is particularly important
in manufacturing systems with unfavorable disturbances. There are two kinds
of system disturbances in the systems under consideration: (1) unfavorable
internal disturbances - usually associated with unfavorable machine capacity
fluctuations; (2) unfavorable external disturbances such as fluctuations
in demand.
6 Risk-Sensitive Hierarchical Controls
The basic idea of the risk-sensitive control is to consider a risk-sensitive
cost function that penalizes heavily on costs associated with large values
of state and control variables. Typically an exponential-of-integral cost
criterion is considered. Such cost functions penalize heavily, state trajectories
and controls which give large values to the exponent. Related literature
on risk-sensitive and robust controls can be found in Whittle
(1990), Fleming and McEneaney (1995),
Barron
and Jensen (1989), and references therein. For details of models discussed
in this section, see Zhang (1995).
As the rate of fluctuation of the production capacity process goes to
infinity, we show that the risk-sensitive control problem can be approximated
by a limiting problem in which the stochastic capacity process can be averaged
out and replaced by its average. We also show that the value function of
the limiting problem satisfies the Isaacs equation of a zero-sum, two-player
differential game. Then, we use a near optimal control of the limiting
problem to construct a nearly optimal control for the original risk-sensitive
control problem.
In Section 6.1 we consider risk-sensitive
hierarchical controls with discounted costs. In Section 6.2
we study risk-sensitive hierarchical controls with average costs.


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