Heuristic Scheduling On Unrelated Parallel Machines With Applications In The Textile Industry

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.