1,721,012 research outputs found
A stochastic cross-efficiency data envelopment analysis approach for supplier selection under uncertainty
No full textThis paper addresses one of the key objectives of the supply chain strategic design phase, that is, the optimal selection of suppliers. A methodology for supplier selection under uncertainty is proposed, integrating the cross-efficiency data envelopment analysis (DEA) and Monte Carlo approach. The combination of these two techniques allows overcoming the deterministic feature of the classical cross-efficiency DEA approach. Moreover, we define an indicator of the robustness of the determined supplier ranking. The technique is able to manage the supplier selection problem considering nondeterministic input and output data. It allows the evaluation of suppliers under uncertainty, a particularly significant circumstance for the assessment of potential suppliers. The novel approach helps buyers in choosing the right partners under uncertainty and ranking suppliers upon a multiple sourcing strategy, even when considering complex evaluations with a high number of suppliers and many input and output criteria
A cross-efficiency fuzzy Data Envelopment Analysis technique for performance evaluation of Decision Making Units under uncertainty
No full textThe paper presents a novel cross-efficiency fuzzy Data Envelopment Analysis (DEA) technique for evaluating different elements (Decision Making Units or DMUs) under uncertainty. In order to evaluate the performance of several DMUs while dealing with uncertain input and output data, the presented technique employs triangular fuzzy numbers. A fuzzy triangular efficiency is associated to each DMU through a cross evaluation obtained by a compromise between suitably chosen objectives. Results are then defuzzified to provide a ranking of the DMUs. The proposed method is applied to the performance evaluation of healthcare systems in a region of Southern Italy. The DMU data uncertainty derives from ongoing reforms and the reported assessment is conducted firstly in order to evaluate and rank the efficiency of the considered healthcare systems, and subsequently to assess the evolution of the performance of one of the most affected among these DMUs by the reform plans. The case study demonstrates 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
Using cross-efficiency fuzzy Data Envelopment Analysis for healthcare facilities performance evaluation under uncertainty
No full textaddress the problem of healthcare systems performance evaluation under uncertainty by a cross-efficiency fuzzy Data Envelopment Analysis (DEA) technique. Triangular fuzzy numbers are employed to deal with uncertain data. More precisely, a fuzzy triangular efficiency is associated to each hospital/ward through a cross-evaluation by a compromise between objectives. Results are defuzzified to obtain the ranking. The method is applied to evaluate hospitals in a region of Southern Italy and estimate the temporal evolution of the performance of one of them, showing the ease of application and usefulness in validating and planning healthcare reforms. © 2013 IEEE
La valutazione incrociata dei fornitori in condizioni di incertezza con il metodo della Data Envelopment Analysis
No full textIl lavoro affronta uno degli obiettivi principali della funzione
di acquisto in una supply chain, ovvero la selezione ottima dei
fornitori. Viene presentata una metodologia basata sulla nota
tecnica di valutazione incrociata dell’efficienza detta Data
Envelopment Analysis (DEA), che utilizza l’approccio della
simulazione Monte Carlo per gestire l’incertezza nel processo
di fornitur
A cross efficiency fuzzy Data Envelopment Analysis technique for supplier evaluation under uncertainty
No full textWe present a novel cross efficiency fuzzy Data Analysis (DEA) technique for supplier selection under uncertainty. In order to deal with uncertain input and output suppliers data, triangular fuzzy numbers are employed. A fuzzy triangular efficiency is associated to each supplier through a cross evaluation by a compromise between objectives. The results are defuzzified and a supplier ranking is determined. The method is applied to the evaluation of a set of candidate suppliers of an Italian SME, showing the ease of application and discriminative power among suppliers
A Nash equilibrium simulation model for the competitiveness evaluation of the auction based day ahead electricity market
No full textThis paper presents a simulation model based on the Nash equilibrium notion for the auction based day ahead electricity generation market. The presented model enhances a previous formalism proposed in the related literature by employing empirical data distributions of the market clearing price as registered by the market authority (e.g. the Independent System Operator). The model is effective when power suppliers with different generation capacities are considered, differently from the starting model that unrealistically assumes equal capacities. The proposed approach aims at evaluating the electricity market competitiveness with regard to the bidder strategies in order to prevent their anticompetitive actions. The framework is applied to a real data set regarding the Italian electricity market to enlighten its effectiveness in different scenarios, varying the number and capacity of participating bidders. The model can be employed as a basis for a decision support tool both for market participants (to define their optimal bidding strategy) and regulators (to avoid collusive strategies)
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