This project consists in two parts due to the double degree in Computer Engineering and Administration and Business Management requirements. The first one presents and approaches a stochastic mixed integer linear programming model. The model conceived for pig production planning has the objective to optimize the entire pig supply chain according to the number of farms operating for the same company or cooperative. The model maximizes the revenue calculated from the income of sales to the abattoir and the production costs. Production costs depends on each type of farm involved in the process. Factors like farm capacity, trucks available and transportation costs are considered, among others. The model considers a medium-term planning horizon and specifically provides optimal transport planning in terms of number of animals to be transported from one facility to another and the number of trucks to do so. The algebraic modelling software OPL studio, in combination with the solver CPLEX both from IBM ILOG have been used to solve the model and study its properties and behaviour. In addition, a potential improvement in the execution time has been sought considering that a real application of the model is expected. This has been done through the generation of instances variating the number of farms that take part in each execution. The instances are required to apply a genetic algorithm on the search space defined by the cartesian product of the solver domains. Once a given time limit elapses, it returns the value of the parameters for which it has had a superior performance on average over the group of instances. Then, the results are analysed and the variations of the model execution time are studied. The second part of the project consists in developing a decision support system (DSS), which takes form of an application that approaches and facilitates the use of the model in order to provide each user a personalized solution. In addition, a friendly interface displays a google maps personalized instance presenting all the facilities that users, companies and cooperatives or even farmers, have introduced to the system. The information introduced will be used to run the model and generate the specific solution for the user. In addition, the interface also allows users to introduce new facilities to the system and visualize their current information and characteristics.