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We present a novel cross efficiency fuzzy Data Envelopment 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.

This paper presents a general modeling framework for Intermodal Freight Transport Terminals (IFTTs). The model allows simulating and evaluating the performance of such key elements of the intermodal transportation chain. Hence, it may be used by the decision maker to identify the IFTT bottlenecks, as well as to test different solutions to improve the IFTT dynamics. The proposed modeling framework is modular and based on timed Petri Nets (PNs), where places represent resources and capacities or conditions, transitions model inputs, flows, and activities into the terminal and tokens are intermodal transport units or the means on which they are transported. The model is able to represent the different types of existing IFTTs. Its effectiveness is tested first on an example from the literature and then on a real case study, the railroad inland terminal of a leading Italian intermodal logistics company, showing its ease of application. In the real case study, using the proposed formalism we test the as-is IFTT performance and evaluate alternative possible to-be improvements in order to identify and eliminate emerging criticalities in the terminal dynamics.

We present a Decision Support System (DSS) for real-time management of railway networks. The DSS employs a mathematical programming approach addressing traffic rescheduling under unexpected disturbances in a mixed-(single- and double-) tracked network. The DSS simulates the network behavior with the mathematical programming model based on the railway topology and constraints, rescheduling the timetable in real time, detecting and solving conflicts in the network. The DSS is applied to a real data set related to a large portion of a regional network in Southern Italy.

This paper presents a general modelling framework for intermodal freight transport terminals. The model allows evaluating the operational performance of such transportation systems, assessing the efficiency level of the terminal and identifying its bottlenecks by suitable performance indices. Moreover, it allows evaluating different solutions to the identified criticalities. The proposed framework is modular and based on timed Petri nets: places represent resources and capacities or conditions, transitions model inputs, flows and activities into the terminal, and tokens are intermodal transport units or the means on which they are transported. A simulation of a case study shows the model effectiveness.

This paper focuses on modelling and performance evaluation of an Intermodal Freight Transport Terminal (IFTT), the rail-road inland terminal of a leading Italian intermodal logistics company. The IFTT is regarded as a discrete event system and is modelled in a timed Petri net framework. By means of suitable performance indices, we simulate the Petri net model and evaluate the operational performance of the transport system. This allows assessing the efficiency level of the terminal and identifying its criticalities and bottlenecks. Further, the model allows evaluating different solutions to the recognized criticalities under alternative scenarios (e.g., when inflow traffic increases and congestions may occur).

Objective To identify differences in the management and outcome of patients with central nervous system metastases from epithelial ovarian cancer. Methods The clinical and pathologic characteristics, treatment, and outcome of 23 patients with brain metastases from epithelial ovarian cancer who were treated during 1982–1994 were compared with those of 20 patients treated during 1995–2010 at the same center. Results No differences were found in terms of primary tumor characteristics, time interval from ovarian cancer diagnosis to brain involvement diagnosis, sites of metastasis, and presence of extracranial disease. The main difference between the 2 groups was the therapeutic approach. During 1982–1994, most patients received radiotherapy only, whereas most patients during 1995–2010 underwent surgical resection followed by radiotherapy and/or chemotherapy. The duration of survival during 1982–1994 was 5 months, which was significantly shorter than the duration of survival (18 months) during 1995–2010. Conclusion An aggressive multimodal treatment approach might prolong the survival of patients with brain involvement from ovarian cancer.

The paper addresses the optimal design of the last branch of the supply chain, i.e., the Distribution Network (DN). We extend a deterministic optimization model previously proposed by the authors, using fuzzy numbers and fuzzy logic to take into account uncertainty in the DN model and in the DN design. Hence, a procedure employing digraph modeling and fuzzy mixed integer linear programming is presented to select the optimal DN configuration. To show the method effectiveness, the optimization model is applied to a case study.

The paper addresses the optimal design of the last branch of the supply chain, i.e., the Distribution Network (DN), starting from manufacturers till the retailers. Considering a distributed system composed of different stages connected by material links labeled with suitable performance indices, a procedure employing digraph modeling and mixed integer linear programming is presented to select the (sub)optimal DN configuration. The optimization model is applied under structural constraints to a case study describing the distribution chain of a large enterprise of southern Italy producing consumer goods. The problem solution provides different structures allowing the improvement of the DN flexibility and performance.