| dc.description.abstract | "Heuristic scheduling on unrelated parallel machines with applications in the textile
industry" is the topic of this thesis, which aims to develop a model that considers
consideration variables including who, what, and where in independent and unrelated
parallel machines. With the application of the suggested model, industries may
effectively plan and manage their workforce, resulting in optimal machinery utilization
and lower operational costs. In particular, this work focuses on scheduling n jobs with
a one-to-one correlation between machines and agents on m independent parallel
machines managed by a agents. In this case, a is always equal to m. The objective
function is to reduce the schedule's maximum completion time (makespan) while
taking setup time—which varies depending on the agent, machine, and task
sequence—into consideration. | en_US |
