The subject of this master thesis is the creation of a computer program, which aims to optimize the sequence of order fulfilment in the process of pig carcass decomposition. A combined algorithm, which consists of a genetic and a local search algorithm, performs the order calculation. In the first part of this thesis the physical process of pig carcass separation is described. This is followed by an examination of the project-related facilities and the associated problems. The data for the planing procedure are delivered by two additional modules, called product tree calculation and customer assignment. A final module deals with those parts of the pigs, which were not included in customer orders. The theoretical part of the thesis starts with introducing commonly used terms with respect to evolutionary algorithms. The family of evolutionary algorithms consists, in addition to the aforementioned genetic algorithms, of evolution strategies, evolutionary programming and genetic programming. These four classic variants share the same basic structure. Their unique features are stated in the respective chapters. Subsequently possible variations of genetic algorithms are discussed in more detail. This concerns different shapings of representations, populations, selection and variation operators. The focus is set on operators, which can be applied to combinatorial optimization problems. The theoretical part concludes with an introduction to local search and memetic algorithms. Finally, the provided data set is presented and the developed java program is explained. Furthermore, the problem specific solution quality of two implemented memetic algorithms is compared.