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To reduce the computational complexity per step from O(n²) to O(n) for optimization based on quadratic surrogates, where n is the number of design variables.

Applying nonlinear optimization strategies directly to complex multidisciplinary systems can be prohibitively expensive when the complexity of the simulation codes is large. Increasingly, response surface approximations (RSAs), and specifically quadratic approximations, are being integrated with nonlinear optimizers in order to reduce the CPU time required for the optimization of complex multidisciplinary systems. For evaluation by the optimizer, RSAs provide a computationally inexpensive lower fidelity representation of the system performance. The curse of dimensionality is a major drawback in the implementation of these approximations as the amount of required data grows quadratically with the number n of design variables in the problem. In this paper a novel technique to reduce the magnitude of the sampling from O(n²) to O(n) is presented.

The technique uses prior information to approximate the eigenvectors of the Hessian matrix of the RSA and only requires the eigenvalues to be computed by response surface techniques. The technique is implemented in a sequential approximate optimization algorithm and applied to engineering problems of variable size and characteristics. Results demonstrate that a reduction in the data required per step from O(n²) to O(n) points can be accomplished without significantly compromising the performance of the optimization algorithm.

A reduction in the time (number of system analyses) required per step from O(n²) to O(n) is significant, even more so as n increases. The novelty lies in how only O(n) system analyses can be used to approximate a Hessian matrix whose estimation normally requires O(n²) system analyses.

This study aims to present diverse proposals for the measurement of tourism destination competitiveness that serve as alternatives to the travel and tourism competitiveness index (TTCI).

The proposal includes principal component analysis, the DP2-distance method, goal programming, data envelopment analysis and the Borda count. The study evaluates 17 destinations from Central America and the Caribbean.

These include the feasibility that the methodologies provide reliable competitiveness rankings and the possibility of using less information due to the strength of the statistical methodologies. International tourist arrivals, income from international tourism and travel and tourism contribution to the gross domestic product could be used as approximations of tourism destination competitiveness.

The main limitation is the absence of major destinations from the region that constitutes fierce competitors.

New aggregation methods can build composite indicators for competitiveness measurement and their presentation in a more comprehensible way.

The results serve as an alternative for countries that have yet to be considered in international tourism competitiveness comparisons.

A better explanatory power of the proposed index is given, thanks to their decomposition capacity and the reduction of the limitations of the original TTCI. Moreover, the proposals facilitate the inclusion of external information or the execution of a completely objective methodology.

本研究旨在为衡量旅游目的地竞争力提出多样化的建议, 并作为旅行和旅游竞争力指数的替代方案。

该提案包括主成分分析、DP₂ 距离方法、目标规划、数据包络分析和 Borda 计数。 该研究评估了中美洲和加勒比地区的 17 个目的地。

结果包括这些方法提供可靠的竞争力排名的可行性, 以及由于统计方法的优势而使用较少信息的可能性。 国际旅游人数、国际旅游收入以及旅行和旅游对 GDP 的贡献可以用作旅游目的地竞争力的近似值。

主要局限是该地区没有竞争激烈的主要目的地。

新的聚合方法可以为竞争力测量建立综合指标, 并以更易于理解的方式呈现。

结果可作为国际旅游竞争力比较中, 衡量尚未考虑国家的替代方案。

由于其分解能力和原始 TTCI 限制的减少, 所提出的指数具有更好的解释力。 此外, 这些建议有助于纳入外部信息及执行完全客观的方法。

El presente estudio busca presentar diversas metodologías para medir la competitividad de los destinos turísticos, de modo que sirvan como alternativa al Índice de Competitividad de Viajes y Turismo.

La propuesta incluye Análisis de Componentes Principales, el método de distancia DP₂, Programación por Metas, Análisis Envolvente de Datos y el Recuento de Borda. Se analizan 17 destinos de Centro América y el Caribe.

Estos incluyen la validez de las metodologías para obtener rankings de competitividad fiables y la posibilidad de emplear menor cantidad de información, dadas las fortalezas de los procedimientos estadísticos propuestos. Las Llegadas de Turistas Internacionales, los Ingresos por Turismo Internacional, y la Contribución del Turismo al PIB podrían ser buenas aproximaciones para medir competitividad turística

La principal limitación es la ausencia de destinos importantes de la región, que se consideran importantes competidores.

Novedosos procedimientos de agregación para crear indicadores sintéticos para medir la competitividad turística y su presentación de un modo más comprensible.

Los resultados sirven como alternativa para otros destinos que aún no han sido considerados en comparaciones internacionales de competitividad turística.

Un mejor poder explicativo de los índices propuestos, gracias a su capacidad de descomposición, y la reducción de las limitaciones del índice del WEF. Además, las propuestas facilitan la inclusión de información externa o la ejecución de un método completamente objetivo.

Taking as a case study the city of San Carlos de Bariloche – in northern Patagonia, Argentina – this paper aims to compare its urban structure with previous urbanization models and identify some characteristics of this tourist city that could inspire the construction of an adapted urban model for Latin American tourist cities, particularly those based on natural attractions.

Based on multivariate analysis of population census data and local economic statistics, this paper compares the residential location of different social groups and the location of main economic activities in Bariloche. First, principal component analysis (PCA) is combined with cluster analysis to classify Bariloche’s neighborhoods. Second, different maps are analyzed to study the location of economic activities, in comparison with previous clusters.

The results of this paper show that Bariloche partially adjusts to previous urbanization models, as the landscape and physical environment determine the characteristics of its urban growth, as well as the development of tourist activities. Therefore, this paper then proposes an adapted urban model for the case of Bariloche, which could be also contrasted with other Latin American tourist cities in the future.

Bearing in mind that there is no model of Latin American tourist cities so far, this paper tries to analyze to what extent the assumptions and patterns of previous urban models could be adapted to Latin American tourist cities, such as Bariloche, which base their attractiveness and economic dynamism on its natural physical environment.

Airports are limited in terms of capacity. Particularly, runways can only accommodate a certain number of movements (arrivals and departures) while ensuring safety and determined operational requirements. In such a constrained operating environment, any reduction in system capacity results in major delays with significant costs for airlines and passengers. Therefore, the efficient operation of airports is a critical cornerstone for demand and delay management of the whole air transportation system. Runway scheduling deals with the sequencing of arriving and departing aircraft at airports such that a predefined objective is optimized subject to several operational constraints, like the dependency of separation on the leading and trailing aircraft type or the runway occupancy time. This study aims to develop a model that acts as a tactical runway scheduling methodology for reducing delays while managing runway usage.

By considering real airport performance data with scheduled and actual movements, as well as arrival/departure delays, this study presents a robust model together with an optimization algorithm, which incorporates the knowledge of uncertainty into the tactical operational step. The approach transforms the planning problem into an assignment problem with side constraints. The coupled landing/take-off problem is solved to optimality by exploiting a time-indexed (0, 1) formulation for the problem. The Binary Integer Linear Programming approach allows to include multi-criteria and multi-constraints levels and, even with some major simplifications, provides fewer sequence changes and target time updates, when compared to the usual approach in which the plan is simply updated in case of infeasibility. Thus, the use of robust optimization leads to a protection against tactical uncertainties, reduces delays and achieves more stable operations.

This model has been validated with real data from a large international European airport in different traffic scenarios. Results are compared to the actual sequencing of flights and show that the algorithm can significantly contribute to the reduction of delay, while adhering as much as possible to the operative procedures and constraints, and to the objectives of the airport stakeholders. Computational experiments performed on the case study illustrate the benefits of this arrival/departure integrated approach: the proposed algorithm significantly reduces weighted aircraft delay and computes efficient runway schedule solutions within a few seconds and with little computational effort. It can be adopted as a decision-making tool in the tactical stage. Furthermore, this study presents operational insights regarding demand and delay management based on the results of this work.

Scheduling arrivals and departures at runways is a complex problem that needs to address diverse and often competing considerations among involved flights. In the context of the Airport Collaborative Decision Making programme, airport operators and air navigation service providers require arrival and departure management tools that improve aircraft flows at airports. Airport runway optimization, as the main element that combines airside and groundside operations, is an ongoing challenge for air traffic management.

The purpose of this paper is to set out a methodology for characterising the complexity of air traffic control (ATC) sectors based on individual operations. This machine learning methodology also learns from the data on which the model is based.

The methodology comprises three steps. Firstly, a statistical analysis of individual operations is carried out using elementary or initial variables, and these are combined using machine learning. Secondly, based on the initial statistical analysis and using machine learning techniques, the impact of air traffic flows on an ATC sector are determined. The last step is to calculate the complexity of the ATC sector based on the impact of its air traffic flows.

The results obtained are logical from an operational point of view and are easy to interpret. The classification of ATC sectors based on complexity is quite accurate.

The methodology is in its preliminary phase and has been tested with very little data. Further refinement is required.

The methodology can be of significant value to ATC in that when applied to real cases, ATC will be able to anticipate the complexity of the airspace and optimise its resources accordingly.

In this chapter, we discuss how an outside writing program was able to assist the stakeholders at a local middle school and the story behind the leaders involved in the process. This program was part of a larger system of “interventions” geared toward improving student success and teacher efficacy. Traditional interventions (after-school tutorials, grouping by state assessment scores, test-taking strategies) were viewed as lacking when it came to their impact on the campus's mostly students of color. Knowing the potential impact of a solid reading and writing program on urban youth, the faculty on the campus teamed with a Writers in the Schools (WITS) writer who proposed several promising practices. The contributions of a professional writer, real-world examples, and ongoing teacher professional development with support contributed to creating a knowledge community of writers that, in addition to creating more scholarship for students and staff, manifested itself in more minority students performing at the highest levels on the state accountability assessments.

The globalization of wine markets together with a prolonged decline in wine consumption, especially in traditional wine-producing countries such as Spain, make it more relevant than ever to study population segments such as female wine consumers. Such segments could contribute to increasing consumption. The purpose of this paper is to investigate the distinctive features of wine consumption according to gender, identifying sociodemographic profiles of female wine consumers and non-consumers in Tenerife (Canary Islands). The Canarian archipelago is one of the Spanish regions with a long tradition in wine production.

This study uses data from a survey carried out on a representative sample of 1,028 Tenerife residents. Independent tests and correspondence analyses were performed. Moreover, an ordered mixed logit model was estimated.

Gender is a determining factor when analysing the frequency of wine consumption. The profiles of female consumers and female non-consumers differ substantially. Considering unobserved heterogeneity in the estimated model also allows us to verify the variability of the effects on the probability of women with the same sociodemographic characteristics having the same consumption pattern.

Non-sociodemographic variables could be considered in this paper.

Marketing strategies should not consider women as a homogenous group.

This study examines in depth the sociodemographic factors that influence the frequency of wine consumption according to gender. It is relevant given the scarcity of studies that analyse these factors. Likewise, unobserved heterogeneity in consumer decisions is taken into account, an aspect that has not been sufficiently considered in wine consumption literature so far.

This paper aims to analyse remotely piloted aircraft system (RPAS) integration in non-segregated terminal airspace. This work aims to identify the potential airspace volumes where a free operation of RPAS can be developed by analysing the airspace design of the terminal airspace.

The methodology considers five crucial elements of the airspace design: obstacles, prohibited, restricted and dangerous zones, aerodrome zones, departing and arriving procedures and visual corridors. Free operation of RPAS is performed in those airspace volumes that no interaction with instrumental flight rules (IFR) flights is expected. Free RPAS airspace volumes are separated through current IFR separation minima.

The results show there is a significant amount of available airspace that RPAS can operate without interaction with conventional aircraft. The more significant risks are allocated by the limitations imposed by departing and arriving procedures in the terminal airspace.

The methodology is applied to medium-dense terminal airspace. This work assumes RPAS can perform visual or instrumental flights.

RPAS is a capital issue for the majority of aviation actors. This work underlay the further development of a methodology regarding airspace design for RPAS in a terminal control area.

Despite the wide dissemination and application of current signature analysis (CSA) in general industry, CSA is not commonly used in the wind industry, where the use of vibration signals predominates. Therefore, the purpose of this paper is to review the use of generator CSA (GCSA) in the online fault detection and diagnosis of wind turbines (WTs).

This is a bibliographical investigation in which the use of GCSA for the maintenance of WTs is analyzed. A section is dedicated to each of the main components, including the theoretical foundations on which GCSA is based and the methodology, mathematical models and signal processing techniques used by the proposals that exist on this topic.

The lack of appropriate technology and mathematical models, as well as the difficulty involved in performing actual studies in the field and the lack of research projects, has prevented the expansion of the use of GCSA for fault detection of other WT components. This research area has yet to be explored, and the existing investigations mainly focus on the gearbox and the doubly fed induction generator; however, modern signal treatment and artificial intelligence techniques could offer new opportunities in this field.

Although literature on the use of GCSA for the detection and diagnosis of faults in WTs has been published, these papers address specific applications for each of the WT components, especially gearboxes and generators. For this reason, the main contribution of this study is providing a comprehensive vision for the use of GCSA in the maintenance of WTs.

The purpose of this paper is to examine the relationship between product innovation and network and their export performance, particularly in trade fair context. Moreover, this paper conducts a comparative study among services/industrial small and medium-sized enterprises (SMEs) and considers the home-country context. Innovation and internationalization are stagnant themes in the recent literature on trade fairs, so they require to be renewed.

The empirical study includes a survey with 341 SMEs’ respondents separated into both industrial/producer and service/other. A conceptual model was developed and examined from three different perspectives: Model A encompasses all surveyed SMEs, Model B includes only industrial/producer SMEs and Model C comprises service/other SMEs. Data analysis happened in two steps. The first step included the structural equation model (SEM) and the assessment of hypotheses (from three different perspectives). Thus, it was possible to make a comparative analysis between the models. In the second step, the ordered logit model (OLM) is used to study relationships between control variables and the criteria variable export performance.

The SEM’s results confirm a conceptual model about a dynamic trajectory that SMEs, mainly industrial/producer, can take advantage of: innovate to networking and networking to export. The results allowed to verify when comparing services/industrial SMEs that the tangibility which characterizes the innovation of industrial SMEs' products contributed significantly to the performance of business networks and exports. The study also reveals, through the OLM, two catalysts for the success of the SME’s export performance: export experience and continued participation in trade fairs. The OLM results also reveal that the size of the companies is not relevant, so trade fairs are marketing tools accessible to any company, regardless of their size. Finally, the study considered home-country context of the surveyed SMEs, which allowed additional interpretations to be drawn.

The study does not reflect the individual's personality in his network capacity and the export performance was measured based on the level of satisfaction and not on real sales results. However, the study provides relevant practical implications and can support future studies.

The study offers important implications for SME. The results reveal that presenting product innovations at trade fairs is a useful tool for SMEs to create networks, which facilitates their export performance, especially for industrial SMEs residing in small economies such as Portugal. This study is also relevant for business associations of industrial SMEs and/or public or semi-public SME promotion agencies.

This paper contributes to the literature on trade fairs, suggesting a new innovation, networking, export (INE) framework to reflect on the participation in international trade fairs. So, this research especially combines product INE performance in a particular context – international trade fairs for SME. It also considers the home-country context of the SMEs, which adds depth to the study. Finally, the comparative study also provides insightful implications for industrial SMEs on how to improve the export performance from trade fairs by leveraging innovation and networking.