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Recent approaches to the service quality evaluation problem are focused on the employment of multi-criteria decisionmaking (MCDM) procedures, since processes related to service quality evaluation presentmeaningful communality elements to MCDM ones. Based on such assumption, in the present paper a new fuzzy MCDMapproach is developed tocomparatively evaluate passenger service quality of the international airports inSicily (Italy). In particular, by incorporating the respondents confidence level and degree of optimism on fuzzy assessments, quality scores of main airport service criteria are estimated, whereas ELECTRE multi criteria decision support methodis proposed to point out theservices quality rankingfor the considered airports, on the basis of which it is performed a strategic benchmarking of service quality. The developed approach represents an effective way to perform evaluation of airports service quality, since it can support airports management to understand and to explain the relatedservice quality ranking in terms of qualityscores of service criteria.

It is herein developed an approach to optimize the maintenance services policy related to a Global Service Contract. In particular, the latter requires the performing of corrective maintenance and replacements of the failed components on a set of equal vehicles of a logistic Company. The tackled problem concerns the determination of an effective opportunistic maintenance policyon the basis of which when a fault occurs, it is replaced the failed component and, depending on the age of the others components, also replacements of others suitable components are performed, even if they are not yet broken, thus saving a substantial amount of system downtime. The problem is mathematically formulated by a constrained partition model aimed at the minimization of the global maintenance cost, which becomes difficult or very hard to solve by mathematical programming approach for large system as the one herein considered. For such reason, a suitable constrained genetic algorithm approach is employed to solve the considered problem. The performed optimization allows to point out components groups on which to perform maintenance actions when a system stop for failure occurs. In particular, a meaningful global maintenance cost reduction, up to 28%, can be obtained, thus demonstrating the effectiveness of the approach proposed.

With refer to a Global Service Contract between a Service Provider and a Logistic Company, the purpose of the present paper is to develop an optimization model aimed to minimize the maintenance related total cost. In particular, such contract requires the supplying of a mandatory set of corrective maintenance services on a set of equal vehicles, in a fixed time horizon. The considered problem is formulated by a non-linear constrained mathematical model that, for large practical systems as the one herein considered, becomes difficult or very hard to solve by mathematical resolution approach. For this reason, a specific resolution approach based on a constrained genetic algorithm is herein developed to solve the treated problem. The obtained results show that meaningful cost reductions can be achieved by using the proposed approach.

Customer satisfaction analyses are deeply based on customers' judgments and as consequence, they can be characterized by a certain degree of uncertainty generally ascribed to coexistence of three relevant aspects: vagueness, imprecision and subjectivity. In the present paper, a methodology able to handle such uncertainty, based on the ServQual discrepancy paradigm and that uses in combined manner the AHP method and the Fuzzy Sets Theory is proposed in order to overcome limitations of the traditional service evaluation approaches. Subsequently, by considering the Italian public transit service sector, a service quality analysis is conducted and the overall transit service quality structure is described. Finally, by using the developed methodology, the evaluation of customer satisfaction for the public urban transit service provided in the city of Palermo (Italy) is performed, and the prioritizing of its critical to quality service attributes is carried out. The obtained results show that only few service attributes play an important role in performing a quality transit service.

Different approaches are being developed to improve the differentiation of Leishmania genus using biochemical and molecular methods. In this study, 11 independent polymorphic microsatellites were used for the typing of strains of L. infantum isolated in Sicily. Polymerase chain reaction was employed to amplify the microsatellites contained in 12 DNA regions selected from among more investigated loci. A total of 51 isolates of L. infantum from dogs were tested by using the same locus panel. The products were successively analysed using an automatic sequence detector (ABI PRISM 3130 AB), to discover relevant microsatellite polymorphisms. It was possible to discriminate between MON-1 and non-MON-1 groups. Moreover, the method permitted to distinguish various genotypes of L. infantum isolates within each zymodema. Model- and distance-based analyses of the data set showed comparable results. The frequency of heterozygosity in the alleles analysed varied extremely between the different groups of isolates. As the method exhibits a high level of discrimination, it is suitable for characterization of closely related strains in epidemiological studies.

Manufacturing tiny components into gigantic structures seems unimaginable without welding connections, whether it is for materials, parts, structures, or equipment. In the recent competitive market scenario, manufacturing industries are desperately looking for a viable alternative to fusion-based conventional material joining technologies, to improve upon cost-effectiveness along with performance. The present investigation is to evaluate the performance of structural steel thick plate joints prepared by advanced solid-state friction stir welding (FSW) over conventional metal active gas welding (MAG). The FSW experiments were carried out with different tool designs and configurations. The outcomes were evaluated in terms of microstructural integrity and mechanical joint resistance. Impressive results were obtained with FSW joints, characterized by an almost defect-free microstructure with a leaner heat-affected zone and higher joint resistance as compared to conventional MAG-welded joints.

Background and aim To evaluate the prevalence of subclinical cardiovascular (CV) abnormalities in systemic lupus erythematosus (SLE) stratified according to SLE-related organ damage using the Systemic Lupus International Collaborating Clinics (SLICC) damage index. Methods and results We selected SLE patients without clinically overt CV events (n = 45, 56% with SLICC = 0, 44% with SLICC = 1–4). CV evaluation was performed using cardiac and vascular echo-Doppler techniques. Post-ischemic flow-mediated dilation (FMD) over nitroglycerine-mediated dilation (NMD) of the brachial artery 0 (p = not significant (NS)). In particular, the prevalence of carotid atherosclerosis (28% vs. 16%), of LV hypertrophy (12% vs. 6%) and of LV wall motion abnormalities (15% vs. 12%), of low global arterial compliance (18% vs. 10%), prevalence of aortic regurgitation (30% vs. 18%) and/or aortic valve fibrosclerosis (10% vs. 8%), FMD 0 and in those with SLICC = 0 (all p = NS). Of the SLE patients without carotid atherosclerosis, LV hypertrophy, low arterial compliance, LV wall motion abnormalities and aortic regurgitation (n = 17), endothelial dysfunction was detected in 50% of those with SLICC = 0 (6/12) and in 40% of those with SLICC > 0 (2/5, p = NS). Conclusions SLE patients with SLICC = 0 often have an elevated CV risk profile due to subclinical manifestations of CV disease detectable by cardiac and vascular echo-Doppler evaluations.

Background Leishmaniasis is one of the most important vector-borne diseases and it represents a serious world health problem affecting millions of people. High levels of Leishmania infections, affecting both humans and animals, are recognized among Italian regions. Among these, Sicily has one of the highest prevalence of Leishmania infection. Methodology/Principal Findings Seventy-eight Leishmania strains isolated from human and animal samples across Sicily, were analyzed for the polymorphic k26-gene and genotypes were assigned according to the size of the PCR products. A multilocus microsatellite typing (MLMT) approach based on the analysis of 11 independent loci was used to investigate populations structure and genetic diversity of the isolated strains. Six L. infantum reference strains were included in the analysis for comparison. Bayesian clustering analysis of microsatellite data showed that all the isolated strains clustered in two genetically distinct populations, corresponding to human and canine isolates respectively. A further subdivision was observed between the two main groups, giving a good correlation between human strains and their geographic origin, conversely canine population showed a great genetic variability diffused in the territory. Conclusions/Significance Among the 78 Leishmania isolates, K26 analysis detected 71 samples (91%) as MON-1 zymodeme, confirming it as the predominant strain in Mediterranean area and 7 human samples (9%) as non-MON-1. MLMT gives important insights into the epidemiology of leishmaniases and allows characterization of different strains to a higher resolution than possible with zymodeme typing. Two main populations presented a strong correlation respect to the different hosts, exhibiting a co-circulation of two distinct populations of L. infantum. The population found in infected humans exhibited a correlation with geographic origin. These clusters could represent a geographically restricted population of strains with the same or related genotypes. This study can contribute to an understanding of Leishmania epidemiology, including the spread of reservoirs and sand fly vectors in the different foci of infection, characterizing parasites within the different hosts., Author summary High levels of Leishmania spp. infections affecting both humans and animals are recognized among Italian regions; in particular, Sicily is an endemic area for Leishmania infantum. In this study 78 Sicilian L. infantum strains isolated from humans and dogs were assessed to investigate their biodiversity by genetic tools. Results were compared with 6 L. infantum reference strains included in the analysis. The evaluation of K26 genetic markers identified 91% of samples as belonging to the MON-1 zymodeme, confirming it as the predominant strain in the Mediterranean area and 9% of the samples–all isolated from humans–as non-MON-1. Multilocus microsatellite typing has proven to be a powerful tool to discriminate strains showing all the isolated strains clustered in two genetically distinct populations, corresponding to human and canine isolates, respectively. A further subdivision was observed between the two main groups, giving in the human population a correlation between microsatellite profile and geographical origin. Our results demonstrate that genetic tools are able to discriminate Leishmania strains and to give useful insights into the epidemiology of leishmaniasis, raising questions on the role of dogs as main reservoirs for human leishmaniasis in the Sicily region.

A novel two-step knowledge-based exploratory framework is proposed in this paper for studying quality of Italian Mobile Telecommunication Services (MTSs). Particularly, the Delphi technique is initially considered to finalize an overall quality structure of MTSs features, indicators and drivers, herein described on the basis of a comprehensive review of the fundamental references for the field, and also to select the key elements with reference to the Italian context. At the second step, selected key elements are prioritized via the Analytic Hierarchical Process (AHP) method according to viewpoints of the fundamental stakeholders for the sector. Furthermore, possible uncertainty and ambiguity of involved experts at this step of the study are addressed via a linguistic comparison scale represented by fuzzy numbers. Results of the first step revealed that the quality structure of Italian MTSs includes 15 key indicators with reference to four key MTSs quality features and 7 key drivers. On the other hand, results of the second step pointed out that tangible aspects represents the fundamental key MTSs quality feature, whereas network population coverage, price of data services, and internet network performance represent the crucial key indicators. In addition, technological resources and technological innovation as well as informational resources constitute the most important key quality drivers of Italian MTSs. Obtained results may be of interest for MTSs managers and decision makers as well researchers of the field offering important suggestions as to how to evaluate and improve quality of MTSs

Nowadays, both continuous and discontinuous operating systems require higher and higher reliability levels in order to avoid the occurrence of dangerous or even disastrous consequences. Accordingly, the definition of appropriate maintenance policies and the identification of components to be maintained during the planned system’s downtimes are fundamental to ensure the reliability maximization. Therefore, the present paper proposes a mathematical programming formulation of the selective maintenance problem with the aim to maximize the system’s reliability under an uncertain environment. Specifically, the aleatory model related to the components’ failure process is well known, whereas some model parameters are affected by epistemic uncertainty. Uncertain parameters are hence gathered from experts in an interval form, and the Dempster-Shafer Theory (DST) of evidence is proposed as a structured methodology to properly deal with the interval-valued experts’ opinions. An exact and efficient algorithm is finally used to solve the optimization model.

An innovative combined evaluation approach is proposed in the present paper to deal with the issue of the performance measurement and comparison of Urban Waste Management (UWM) services in the context of cities. The ELECTRE III method is initially considered as tool able to execute a multi-criteria analysis aimed at ranking UWM systems based on their integration and sustainability levels. The latter are comprehensively evaluated via the recently developed “Wasteaware” Integrated and Sustainability Waste Management indicators framework, which takes into account physical components and governance aspects of UWM systems. Then, on the basis on ELECTRE III results, a practical gaps investigation is developed to comparatively highlight service weaknesses to be addressed to pursue more equity concerning integration and sustainability in the considered context. The issue is particularly relevant in light of the multi-dimensional nature and the substantial complexity of UWM systems, as well as for the high criticality level assumed by these systems in recent years. The proposed combined evaluation approach is applied to an empirical case which regards the UWM systems of the Optimal Territorial Ambit of Palermo (Sicily). In the considered context, results highlight how stakeholders' participation in decision-making activities represents a crucial factor to pursue shared and coordinated strategies in line with integration and sustainability principles. Moreover, seventeen measures involving operational, environmental, socio-economic as well as administrative waste management aspects are selected from a comprehensive list of measures aimed at waste management integration and sustainability, and then implemented in the investigated context. Through these measures, the resulting services criticalities can be evaluated and properly addressed, and new required processes can be designed.

In this paper a new approach was proposed so as to comparatively evaluate the quality of service alternatives. In particular, a fuzzy extension of the ServPerf service conceptual model was considered to estimate quality scores of fundamental service criteria, whereas the non-compensative multi-criteria decision-making ELECTRE III method was employed to point out the quality ranking of service alternatives on the basis of which the comparative service quality analysis was performed. In order to show the effectiveness of the proposed approach, an empirical study concerning service quality evaluation of the three international airports in Sicily (Italy) was conducted with detailed proposals for passenger service improvement. The results showed that only few key service aspects played a focal role in quality airport service. Moreover, the effects on the evaluation of service quality, arising from customers' uncertainties, were computed, thus demonstrating the effectiveness of the proposed approach.

A novel fuzzy-based approach which combines ELECTRE III along with the Importance-Performance Analysis (IPA) is proposed in the present work to comparatively evaluate the service quality in the public healthcare context. Specifically, ELECTRE III is firstly considered to compare the service performance of examined hospitals in a noncompensatory manner. Afterwards, IPA is employed to support the service quality management to point out improvement needs and their priorities. The proposed approach also incorporates features of the Fuzzy Set Theory so as to address the possible uncertainty, subjectivity and vagueness of involved experts in evaluating the service quality. The model is applied to five major Sicilian public hospitals, and strengths and criticalities of the delivered service are finally highlighted and discussed. Although several approaches combining multi-criteria methods have already been proposed in the literature to evaluate the service performance in the healthcare field, to the best of the authors’ knowledge the present work represents the first attempt at comparing service performance of alternatives in a noncompensatory manner in the investigated context.

In recent years, the attention that the European Community has focused on the education sector has produced a new university commitment addressed to quality aspects for all education related services. In fact, a quality oriented service requires excellence in the design and planning of service activities, as well as during its delivering and also for the adopted service performance evaluation method. However, considering that service performance evaluations are deeply based on stakeholders' judgments, they can be characterized by possible uncertainties related to incompleteness for partial ignorance, imprecision for subjectivity and even vagueness. Therefore, under these conditions, unreliable results can be obtained by widely considered service analysis methods. In the present paper, a method based on a recent extension of the ServQual model and that uses in combined manner the Fuzzy Set Theory and the Analytic Hierarchy Process method is proposed to effectively handle uncertainty in service performance analyses. In particular, the Fuzzy Set Theory is considered to deal with such uncertainty, whereas the AHP method is adopted as tool to estimate the importance weights of the strategic service attributes. Subsequently, the strategic analysis of the service value tree related to the Management Engineering program at the University of Palermo (Italy) is performed by using the proposed method. The performed service analysis allows the most influencing service performance factors to be captured and commented upon. Finally, the obtained results show that the professors' perception of service quality meaningfully influences the overall service performance level.

The problem tackled by the present paper concerns the selection of the elements of a repairable and stochastically deteriorating multi-component system to replace (replacements configuration) during each scheduled and periodical system stop within a finite optimization cycle, by ensuring the simultaneous minimization of both the expected total maintenance cost and the system unavailability. To solve the considered problem, a combined approach between multi-objective optimization problem (MOOP) and multi-criteria decision making (MCDM) resolution techniques is proposed. In particular, the @e constraint method is used to single out the optimal Pareto frontier whereas the ELECTRE III multi-criteria decision support method is proposed to support the selection of the replacements configuration that represents the best compromise among the considered objectives. The proposed approach is sequentially applied at each scheduled system stop by allowing the dynamic updating of the information about the decisional context in which the decision maker has to operate. To illustrate the whole procedure a numerical case study is solved for different hypothesized scenarios related to the importance attributed by the decision maker to the system unavailability and the maintenance cost objectives.

A conceptual model of the Academic Library (AL) service quality is hypothesized in the present article, and then validated and analyzed by a novel evaluation approach. Specifically, the conceptual model integrates the fundamental attributes of the canonical AL service together with those more relevant of the new and widely considered AL Electronic Service (e-services). As concerns the evaluation approach, it incorporates the Fuzzy Sets Theory (FST) so as to deal with the students’ uncertainty over their own judgments on the AL service quality and a Structural Equation Model (SEM) to validate the conceptual model and to determine the key drivers of the AL service quality. The effectiveness of the proposed approach is proved by an empirical study concerning the AL of the Polytechnic School of the University of Palermo (Italy). Data collected via a survey involving more than 600 students are used, and the key drivers of the AL service quality are found out. Particularly, the obtained results reveal that Collections and materials represents the main driver of the AL service quality followed by Infrastructure and Access to the service, whereas Staff plays the fundamental role of interface between AL service aspects and students’ needs and necessities.

The objective of a maintenance policy generally is the global maintenance cost minimization that involves not only the direct costs for both the maintenance actions and the spare parts, but also those ones due to the system stop for preventive maintenance and the downtime for failure. For some operating systems, the failure event can be dangerous so that they are asked to operate assuring a very high reliability level between two consecutive fixed stops. The present paper attempts to individuate the set of elements on which performing maintenance actions so that the system can assure the required reliability level until the next fixed stop for maintenance, minimizing both the global maintenance cost and the total maintenance time. In order to solve the previous constrained multi-objective optimization problem, an effective approach is proposed to obtain the best solutions (that is the Pareto optimal frontier) among which the decision maker will choose the more suitable one. As well known, describing the whole Pareto optimal frontier generally is a troublesome task. The paper proposes an algorithm able to rapidly overcome this problem and its effectiveness is shown by an application to a case study regarding a complex series–parallel system.

The present paper proposes a novel economic-statistical design procedure of a dynamic c control chart for the Statistical Process Control (SPC) of the manufacturing process of semiconductor devices. Particularly, a non-linear constrained mathematical programming model is formulated and solved by means of the ε-constraint method. A numerical application is developed in order to describe the Pareto frontier, that is the set of optimal c charts and the related practical considerations are given. The obtained results highlight how the performance of the developed dynamic c chart overcome that of the related static one, thus demonstrating the effectiveness of the proposed procedure.

The process capability analysis is a crucial activity to evaluate if the process outcome meets the design specifications. Classically, such analysis is performed by verifying the in-control condition of the process and evaluating suitable capability indices, by assuming the process in-control steady-state condition. However, the in-control period of the process characterizes only a part of the system functioning cycle, the one with the lower defective rate. In particular, the system functioning cycle is also characterized by the out-of-control period, during which a greater defective rate is produced, and such increasing is not considered by the widely adopted capability indices. As consequence, the classical approaches to perform the process capability analysis involves an overestimation of the process capability level. For this reason, in order to overcome the previously described limitation, in the present paper it is proposed a new capability index based on the real defective rate of the process. Thus, such new index is able to estimate the real process capability level. Finally, in order to compare the new index to the conventional Cp capability index, a numerical comparison study related to a process capability analysis is carried out, and the related practical considerations are given.

In the present paper is developed a statistical process control inspection procedure based on a new simple-to-implement and effective double sampling scheme for the c control chart, aimed at the minimization of the number of inspected observation units and warranting fixed levels for the type I and II error risks. In particular, the formulations of the false alarm risk α, the power P of the chart, and the expected number of inspected observation units for the developed inspection procedure are given, whereas a macro of Microsoft Excel is adopted to solve the tackled problem. In order to illustrate the application of the developed approach and to investigate on the influence of several operating parameters, numerical examples are carried out and the related considerations are given. Finally, by comparing the performance of the developed inspection procedure with that of the related classic c chart scheme, meaningful reduction of the number of the inspected observation units can be achieved by adopting the proposed approach.

The present paper proposes an original and innovative cooling law in the field of Simulated Annealing (SA) algorithms. Particularly, such a law is based on the evolution of different initial seeds on which the algorithm works in parallel. The efficiency control of the new proposal, executed on problems of different kind, shows that the convergence quickness by using such a new cooling law is considerably greater than that obtained by traditional laws. Furthermore, it is shown that the effectiveness of the SA algorithm arising from the proposed cooling law is independent of the problem type. This last feature reduces the number of parameters to be initially fixed, so simplifying the preliminary calibration process necessary to optimize the algorithm efficiency.

The main approaches for the television scheduling design are commonly based on the ratings or revenues maximization objective, and thus, only a single optimal solution can be obtained, corresponding to the best result for the considered objective. Therefore, these approaches lead up to the alternative solutions loss which, even if less effective from the ratings or revenues maximization viewpoint, may be more suitable for the decision maker because of better compromise in relation to factors influencing the decision process. Specifically, such a compromise could be achieved through a suitable “trade-off” between these factors, with reference to the decision context in which the decision maker has to operate. The present study concerns the development of a multi-objective approach for the television scheduling design in which ratings and costs are the considered objectives to optimize, because these are the main factors influencing the decision process. In particular, an integer mathematical programming model is formulated and solved, considering as input data forecasted values of show-parts ratings and costs obtained by a suitable forecast engine. Finally, in order to show the employment of the proposed approach, a case study concerning the television scheduling optimization for an Italian TV channel is conducted with detailed practical considerations.

This paper tackles the problem to single out the maintenance actions to be executed on a production system during the planned stop of given length. In detail, from a reliability viewpoint the system is assimilated as a series-parallel multi-component system and the maintenance actions need to maximize the system reliability up to the next planned stop. Moreover, it is assumed that some components reliability values are affected by vagueness within a given range. To solve the considered problem, an exact dynamic programming algorithm suitable to quickly point out the maintenance scheduling is developed and, moreover, it is formulated a proper parameter able to express the robustness of the obtained optimal solutions. Finally, a numerical example with reference to a complex system composed by a large number of components is reported.

Complex nonlinear optimization problems require specific resolution techniques. These problems are often characterized by a solution space that presents many local optima. In these cases, local search algorithms, as the classical descent neighborhood search method, have a heavy drawback: the optimization algorithm generally converges towards a local minimum. To avoid getting trapped in a local minimum, the optimization algorithm must allow to accept worse solutions than the current one. Several kinds of algorithms have been ideated for this purpose and they differ for the acceptance criteria of a pejorative solution. Among such algorithms it is possible to remember the Taboo Search (TS) and the Simulated Annealing (SA). Another class of algorithms, i.e. the Genetic Algorithms (GAs), is based on the evolution of a set (population) of initial solutions. Such classes of algorithms have been applied to several different fields of research. Our interest is addressed to the SA algorithms, in particular to the cooling law, which is fundamental for the SA efficiency. In particular, in the present paper a new cooling law has been proposed for an optimization procedure based on the use of the Simulated Annealing algorithms. The proposal advanced has been tested on the job shop scheduling problem with sequences-dependent set-up times [1] taking into account cases study already treated in the literature [2]. The results show that its utilization allows obtaining a very higher convergence quickness than that one arising from the use of a traditional cooling law. Another strong advantage, that derives from the implementation of algorithms based on the use of the proposal formulation, is the possibility to bypass the classical tuning phase, so determining a further reduction of the global run-time.

The present paper proposes a multi-objective design approach for the c chart, considering in the optimization process of the chart parameters both the statistical and the economic objectives. In particular, the minimization of the hourly total quality related costs is the considered objective to carry out the economic goal, whereas the statistical objective is reached by the minimization the out-of-control average run length of the chart. A mixed integer non-linear constrained mathematical model is formulated to solve the treated multi-objective optimization problem, whereas the Pareto optimal frontier is described by the «-constraint method. In order to show the employment of the proposed approach, an illustrative example is developed and the related considerations are given. Finally, some sensitivity analysis is also performed to investigate the effects of operative and costs parameters on the chart performance

Economic design approaches of control charts are commonly based on the assumption that various cost parameters values and the occurrence risk of assignable causes have to be a priori known with precision. However, in real operative contexts, such parameters can be really difficult to accurately estimate, especially considering costs arising from out-of-control conditions of the process. As consequence, pure economic design approaches can involve chart schemes with low statistical performance. To overcome such limitation, it is herein proposed a multi-objective economic-statistical design approach for an adaptive X-bar chart. In particular, such approach aims at the minimization of both the total quality related costs and the out-of-control average run length, in such a way assuring an optimal trade-off between economic and statistical performance of the related control procedure. Moreover, for a robust design approach, the mean shift is considered as a random variable. A mixed integer nonlinear constrained mathematical model is formulated to solve the treated problem, whereas the Pareto optimal frontier is described by the ε-constraint method. In order to show the employment of the proposed approach, an illustrative example is developed and the related considerations are given. Finally, some sensitivity analysis is also performed to investigate the effects of operative and costs parameters on chart parameters.

The present paper proposes a design approach for a statistical process control (SPC) procedure implementing a c control chart for non-conformities, with the aim to minimize the hourly total quality-related costs. The latter take into account the costs arising from the non-conforming products while the process is in-control and out-of-control, for false alarms, for assignable cause locations and system repairs, for sampling and inspection activities and for the system downtime. The proposed economic optimization approach is constrained by the expected hourly false alarms frequency, as well as the available labor resource level. A mixed integer non-linear constrained mathematical model is developed to solve the treated optimization problem, whereas the Generalized Reduced Gradient Algorithm implemented on the solver of Microsoft Excel is adopted to resolve it. In order to illustrate the application of the developed procedure, a numerical analysis based on a 25 1 V fractional factorial design scheme, to investigate on the influence of several operating and costs parameters, is carried out, and the related considerations are given. Finally, the obtained results show that only few parameters have a meaningful effect on the selection of the optimal SPC procedure.

Evaluation and self-evaluation procedures are commonly used in educational institutions to measure education services and research performance. This chapter describes the main opportunities that evaluation-based approaches can produce to support processes of design and continuous quality improvement in higher education institutions in the light of recent normative measures in Italy to address quality aspects of education services. Subsequently, a new approach – based on the ServQual conceptual model – that evaluates education services is used to carry out a strategic analysis of education services at the management engineering program at the University of Palermo, Italy.