This thesis deals with work scheduling problems and the extension of work scheduling problems with goal programming. In some certain cases, when there is no feasible solution for a scheduling problem, goal programming offers a solution to the problem by prioritizing the goals or the objectives of the problem. Furthermore, this thesis is enhanced by introducing shortage penalties into the models, which improve the relevance of the model. The example used in this thesis, and all of the extensions made to the example are solved with LINGO, which is a software tool that offers solutions to complex work scheduling problems. This thesis proved that models can accommodate real life constraints and can be optimized, and that they can be constructed by the use of linear programming and goal programming. In conclusion, the results of this thesis open the door for the increasing application of optimization techniques in work scheduling problems to provide practical solutions that take into account variations across industries.