Mathematical Optimization of Scheduling Problems: A State-Task Network and Mixed Integer Linear Programming Approach

Sammanfattning

This thesis was carried out on behalf of a Swedish company that performstesting and certification of various products. The aim of the study isto investigate how mathematical optimization can be used to improve thescheduling of limited resources, with a particular focus on test chambers forelectromagnetic compatibility. A model based on the State-Task Network andMixed Integer Linear Programming was compared to a manual schedulingapproach to highlight the differences in performance between the two methods.The results show that the optimized model produces a more efficient schedule,with higher resource utilization, increased revenue and a greater number ofcompleted projects within the same time frame. The study thus demonstratesthat the mathematical method can not only improve operational workflowsbut also provide strategic advantages through more efficient use of existingresources.