NLP for CP
Addressing Constraint Programming with Natural Language Processing
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Correct
predictions are in
blue
. If we detect only a subset of a labelled sentence, we highlight the caught part as
blue
, the missing part
light blue.
False positives
are in
green
and
false negatives
are in
red
.
Problem 040 (Distribution problem with Wagner-Within costs) — Constraint detection
Inventory
theory
provides
methods
for
managing
and
controlling
inventories
under
different
policy
constraints
and
environmental
situations
.
A
basic
distribution
system
consists
of
a
supply
chain
of
stocking
points
arranged
in
levels
.
Customer
demands
occur
at
the
first
level
,
and
each
level
has
its
stock
replenished
from
the
one
above
.
Typically
,
a
holding
cost
per
unit
of
inventory
is
associated
with
each
stocking
point
,
under
the
assumption
that
a
parent
stocking
point
has
a
lower
holding
cost
than
any
of
its
children
.
A
procurement
cost
per
order
is
also
associated
with
each
stocking
point
.
Given
customer
demands
for
each
stocking
point
in
the
first
level
over
some
planning
horizon
of
a
number
of
periods
,
the
problem
is
then
to
find
an
optimal
policy
:
a
set
of
decisions
as
to
when
and
how
much
to
order
for
each
stocking
point
,
such
that
cost
is
minimised
.
The
Wagner-Whitin
form
of
the
problem
assumes
that
the
holding
costs
and
procurement
costs
are
constant
,
and
that
the
demands
are
known
for
the
entire
planning
horizon
.
Furthermore
,
the
stocking
points
have
no
maximum
capacity
and
the
starting
inventory
is
0
.
Problem 040 (Distribution problem with Wagner-Within costs) — Detection of the decisions and objects to be modeled
Inventory
theory
provides
methods
for
managing
and
controlling
inventories
under
different
policy
constraints
and
environmental
situations
.
A
basic
distribution
system
consists
of
a
supply
chain
of
stocking
points
arranged
in
levels
.
Customer
demands
occur
at
the
first
level
,
and
each
level
has
its
stock
replenished
from
the
one
above
.
Typically
,
a
holding
cost
per
unit
of
inventory
is
associated
with
each
stocking
point
,
under
the
assumption
that
a
parent
stocking
point
has
a
lower
holding
cost
than
any
of
its
children
.
A
procurement
cost
per
order
is
also
associated
with
each
stocking
point
.
Given
customer
demands
for
each
stocking
point
in
the
first
level
over
some
planning
horizon
of
a
number
of
periods
,
the
problem
is
then
to
find
an
optimal
policy
:
a
set
of
decisions
as
to
when
and
how
much
to
order
for
each
stocking
point
,
such
that
cost
is
minimised
.
The
Wagner-Whitin
form
of
the
problem
assumes
that
the
holding
costs
and
procurement
costs
are
constant
,
and
that
the
demands
are
known
for
the
entire
planning
horizon
.
Furthermore
,
the
stocking
points
have
no
maximum
capacity
and
the
starting
inventory
is
0
.
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