Fabio Sciancalepore

TL;DR: In this paper, a decision-making tool for supplier selection in public procurement is proposed to help the awarding committee in this difficult task and, at the same time, maintaining a transparent procedure in accordance with governmental procurement regulations and requirements as well as guaranteeing fair and equal evaluation of all bids.

TL;DR: A novel cross-efficiency fuzzy Data Envelopment Analysis (DEA) technique for evaluating different elements (Decision Making Units or DMUs) under uncertainty is presented, demonstrating the model ease of application, its discriminative power among DMUs when compared to a more classical fuzzy DEA approach, and the usefulness in planning and validating targeted reforms in the case of healthcare systems.

TL;DR: A methodology for supplier selection under uncertainty is proposed, integrating the cross-efficiency data envelopment analysis (DEA) and Monte Carlo approach, that is able to manage the supplier selection problem considering nondeterministic input and output data.

TL;DR: In this article, the authors present a probabilistic approach for evaluating and limiting the total cost of purchasing in public tenders awarded according to the Lowest Price (LP) criterion.

TL;DR: The paper enhances a deterministic procedure for DN strategic configuration by employing MOGACOP, a real-valued chromosome MOGA that can be applied to the case of constrained nonlinear function.