Single machine scheduling with overtime in multiproduct assembly environment

In this thesis, two types of problems based on a real-life application for products with multiple assembly groups with different assembly priorities are discussed. The first problem is to determine the daily schedule that will not cause assembly delay by minimizing the amount of overtime under the desired planning horizon and finite capacity constraint for the jobs with sequence dependent setup times. A mixed integer mathematical programming model is proposed for the problem. In the random sample datasets created to measure the model performance, the solution could not be found in a reasonable time as the number of jobs per day increased. Therefore, two decomposition algorithms have been developed for the solution. The second problem is the assignment of jobs to days in a way that minimizes the amount of overtime and does not cause assembly delays for jobs where sequence dependent setup times are not important. Considering the similarity of the problem with the bin packing problem with item fragmentation, the mixed integer mathematical model in the literature was extended and proposed and the solution values were compared.