order-up.1

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.Dd $Mdocdate: August 2 2024 $
.Dt order-up 1
.Os
.Sh NAME
.Nm order-up
.Nd Simplified sequential decision problem of a pizza restaurant ordering
sausage.
.Sh SYNOPSIS
.Nm order-up
.Op Fl tv
.Op Fl d Ar MEAN_DEMAND
.Op Fl s Ar DEMAND_STD_DEV
.Op Fl -num-time-periods Ns = Ns Ar periods
.Op Fl -purchase-cost Ns = Ns Ar cost
.Op Fl -sale-price Ns = Ns Ar price
.Op Fl -theta-max-ceiling Ns = Ns Ar max
.Op Fl -theta-min-ceiling Ns = Ns Ar max
.Sh DESCRIPTION
The
.Nm
program simulates ordering and demand for sausage at a pizza restaurant.
Inspired by Reinforcement Learning in Stochastic Optimization by Warren B.
Powell (2022).

.Bl -tag -width Ds
.It Fl d , -mean-demand Ns = Ns Ar MEAN_DEMAND
Set the mean demand that should be observed during the simulation.
.It Fl s , -demand-std-dev Ns = Ns Ar DEMAND_STD
Set the standard deviation that should be observed during the simulation.
.It Fl -num-time-periods Ns = Ns Ar periods
The number of iterations for which every set of parameters should be tested.
.It Fl -purchase-cost Ns = Ns Ar cost
The purchase cost for one unit of sausage from the supplier.
.It Fl -sale-price Ns = Ns Ar price
The price at which a completed sausage may be sold to a customer.
.It Fl t , -terse
Emit terse output. Overrides the verbose flag.
.It Fl -theta-max-ceiling Ns = Ns Ar max
The highest value the theta-max policy parameter should take during testing.
This value must be greater-than or equal-to the
.Em theta-min-ceiling
option.
.It Fl -theta-min-ceiling Ns = Ns Ar max
The highest value the theta-min policy parameter should take during testing.
This value must be less-than or equal the
.Em theta-max-ceiling
option.
.It Fl v
Emit verbose output. Overrides the terse flag.
.El

.Sh EXIT STATUS
.Nm
will exit with a non-zero value in the event of an error.

.Sh HISTORY
The
.Nm
program was first created during the Summer of 2024. OpenMPI support was added
in September of 2024.
.Sh AUTHORS
.An Ron Dahlgren
.Mt ron@sw.gy