Project selection is a common problem for many companies. Specifically, it consists in identifying which projects should be selected with regard to their economic efficiency, i.e., the projects that maximise the profit they bring in while minimising the cost of the resources consumed. In this paper, we have focused our interest on energy service companies because of the importance of a convenient selection of their projects. In these types of companies, the attractiveness of a project depends on both the profit estimations obtained in simulations of the energy systems to be improved, as well as the probability that the project will be awarded (e.g., in local government bids, where typically several energy service companies compete to win the bid). We propose a new project selection method, especially tailored to energy service companies and based on centralised data envelopment analysis models with limited availability of the resources. This contrasts with all existing project selection methods and allows the proposed approach to make more efficient use of the limited resources. We have applied the model to a real-world case by selecting projects in a Spanish energy service company, showing the benefits of applying this approach, and comparing the results obtained with other data envelopment analysis project selection approaches.
Optimum Selection of Energy Service Company Based on Intuitionistic Fuzzy Entropy and VIKOR Framework