Operations
or
process
scheduling
is
a
problem
whose
relevance
spans
many
different
industrial
and
engineering
fields
such
as
mining,
chemical
production
and
manufacturing
plants.
The
goal
of
process
scheduling
is
to
find
an
optimal
schedule
that
can
efficiently
carry
out
operations
at
minimizing
costs,
in
the
shortest
possible
time
(minimize
turnaround
time),
or
to
maximize
revenue.
Following
schedules
that
are
tailored
to
meet
the
demands
can
greatly
increase
the
overall
efficiency
of
the
operations
or
reduce
overhead.
There
has
been
a
great
amount
of
research
done
in
the
field
of
process
scheduling,
both
for
theoretical
purposes
and
the
practical
reasons
mentioned
above.
However,
the
field
still
remains
rich
as
more
complex
models
made
to
more
closely
resemble
real
world
conditions
are
considered.
My
research
is
focused
around
devising
new
methods
and
strategies
for
solving
a
real
world
scheduling
problem
at
an
analytical
services
facility.
In
practice
with
large
facilities
and
moderately
sized
time
horizons,
finding
optimal
schedules
is
computationally
expensive.
The
goal
of
my
work
is
to
find
“good”
quality
solutions
while
keeping
computational
costs
reasonable
so
that
these
strategies
may
be
employed
in
practice.
Since
it
is
known
that
solving
general
integer
programs
(IPs)
is
NP-hard,
I
am
not
aiming
to
find
algorithms
that
are
necessarily
theoretically
efficient
for
solving
the
problem,
I
am
interested
in
developing
heuristics
that
perform
well
on
the
problem
in
practice.
Thesis:
A
computational
study
of
practical
issues
arising
in
short-term
scheduling
of
a
multipurpose
facility
