Parallel machine scheduling problem with eligibility constraints in a tobacco company

Scheduling is an optimization problem that shows significant results in terms of time, labor/equipment usage and cost for many industrial companies. In recent years, due to decreasing material costs and increasing competition in the market with the development of technology, extra time spent in facilities has become very important. Therefore, planning and scheduling come to the fore in order to get the job done in a shorter time. In this thesis, a scheduling problem is solved with mixed integer linear programming in a cigarette production facility with a parallel machine production flow operating in the tobacco production sector. This study is a real life problem and the data to be used in the solution are taken from the factory where the thesis is carried out. The first purpose of the problem is to minimize the tardiness of jobs and the second one is decreasing completion time. Models used in 92 articles investigated for tardiness and completion time minimization are presented in the literature review. In this thesis, the 19 parallel machines within the enterprise were scheduled according to the incoming filter order and their mathematical model was established. The established mixed integer linear programming model solves using the gurobipy library with Gurobi solver in Python software. As a thesis output, a weekly production plan to be used by the production and production planning team at the beginning of the week presents in the form of a Gantt chart. As another output of the model, when there are deviations from the current plan due to the machines having problems, the model provides a new output and the Gantt chart will be presented to the user again. In this way, a scheduling creates that is user-friendly, flexible and can be shaped according to every business and will also be used by the business by using the appropriate term and resources.