eFat, a prototype of a Cloud decision support system for optimal delivery of fattened pigs to the abattoir

Abstract

This project consists in developing a decision support system and its integration in a cloud platform to offer optimization models as a service integrated in a sole application accessible from different devices. It has two parts due to the double degree in Computer Engineering and Administration and Business Management requirement. The part related to the Administration and Business Management degree is based on a mixed integer linear-programming (MILP) model to support marketing decisions on fattening farms without individual weight control. It includes the development of the running program to solve the MILP model and the assessment for specific factors. The objective is to determine the optimal delivery time and quality bonus of the fattened pigs to the slaughterhouse and thus, getting the best value for the producer. This mathematical model maximizes the revenue and reduces the risk of neglecting opportunity costs by taking into account important key factors such as: homogeneity of the batch, price-grid system, transportation cost, among others. The analysis performed on this study demonstrated the importance of these different factors that affect significantly on the optimal marketing policy of fattening farms, and also in a vertically integrated company. The second part is related to the Computer Engineering degree and concerns the development of a cloud decision support system (cDSS). The cDSS takes form of a client application that allows users to run the mathematical model introduced previously and through it, depict their best marketing decisions for a pig farmer. Through this application, the farmer can store data and update information of the farms, make requests from different devices or visualize an output display of the results obtained from the model.