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Scheduling problems are among the issues which are faced by almost every organization in the world. Optimally scheduling its activities allows a company to make the best use of its resources, let them be financial, human or machines. Unfortunately, it is seldom possible to simply use an existing solution. The aim of this thesis is to develop an MIP-based model taking into account the needs of a Belgian SME in the printing industry. This model’s objective is to be used as a decision making support tool, both on a day-to-day basis as well as for longer term strategic planning. The machine environment is modeled as a flexible flow shop. The extra constraints to take into account are release dates, an extra shared resource (operators) and the fact that some operations can be started at the end of the day and processed during the night without any supervision. The function to minimize is the sum of tardy jobs. The model was tested according to three scenarios using real historic data from the company and the modelling software Aimms. The results show that the tool is usable in practice for instances where at most 5 stages are considered. Unfortunately, I was not able to compare the results obtained with real delivery times. Therefore, I can’t confirm with certainty that the model offers better planning solutions. However, I am optimistic for the possibilities of this tool, especially at a strategic decision making level.

tardy jobs --- print --- operators --- shared resource --- release dates --- MIP model --- flexible flow shop --- scheduling --- Sciences économiques & de gestion > Production, distribution & gestion de la chaîne logistique --- Sciences économiques & de gestion > Méthodes quantitatives en économie & gestion