  This paper addresses a production scheduling problem derived from an
industrial use case, focusing on unrelated parallel machine scheduling with the
personnel availability constraint. The proposed model optimizes the production
plan over a multi-period scheduling horizon, accommodating variations in
personnel shift hours within each time period. It assumes shared personnel
among machines, with one personnel required per machine for setup and
supervision during job processing. Available personnel are fewer than the
machines, thus limiting the number of machines that can operate in parallel.
The model aims to minimize the total production time considering
machine-dependent processing times and sequence-dependent setup times. The
model handles practical scenarios like machine eligibility constraints and
production time windows. A Mixed Integer Linear Programming (MILP) model is
introduced to formulate the problem, taking into account both continuous and
district variables. A two-step solution approach enhances computational speed,
first maximizing accepted jobs and then minimizing production time. Validation
with synthetic problem instances and a real industrial case study of a food
processing plant demonstrates the performance of the model and its usefulness
in personnel shift planning. The findings offer valuable insights for practical
managerial decision-making in the context of production scheduling.
