  Textile industry is becoming a highly competitive area with the increase in
demand for textile products. Since expanding the production capacity is not
always feasible, optimizing the existing system is more practical. In
particular, we consider a felt production system of a textile factory operating
in Turkey in this study. We aim to minimize the production costs by optimizing
machine operating speeds as well as building an efficient production lot sizing
plan within the planning horizon. In this direction, we propose the Lot Sizing
and Machine Speed (LSMS) nonlinear model to determine the optimal unit
processing times and production quantities while minimizing the work-in-process
and end item inventories by changing the machine operating speeds dynamically
according to the demands. Since LSMS nonlinear optimization problem is NP-hard,
we design a Two-Phase heuristic which iteratively processes a linear
programming model by utilizing a commercial solver at each phase. We
intensively test our Two-Phase heuristic via randomly generated demand,
planning horizon and machine-hour capacity scenarios. Our computational
experiments show that the introduced Two-Phase heuristic can find the
local-optimal results in acceptable amount of time.
