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The aim of this paper is to analyse, model, and solve the rescheduling problem in dynamic permutation flow shop environments while considering several criteria to optimize. Searching optimal solutions in multiobjective optimization problems may be difficult as these objectives are expressing different concepts and are not directly comparable. Thus, it is not possible to reduce the problem to a single-objective optimization, and a set of efficient (nondominated) solutions, a so-called Pareto front, must be found. Moreover, in manufacturing environments, disruptive changes usually emerge in scheduling problems, such as machine breakdowns or the arrival of new jobs, causing a need for fast schedule adaptation. In this paper, a mathematical model for this type of problem is proposed and a restarted iterated Pareto greedy (RIPG) metaheuristic is used to find the optimal Pareto front. To demonstrate the appropriateness of this approach, the algorithm is applied to a benchmark specifically designed in this study, considering three objective functions (makespan, total weighted tardiness, and steadiness) and three classes of disruptions (appearance of new jobs, machine faults, and changes in operational times). Experimental studies indicate the proposed approach can effectively solve rescheduling tasks in a multiobjective environment.
Pablo Valledor; Alberto Gomez; Paolo Priore; Javier Puente. Modelling and Solving Rescheduling Problems in Dynamic Permutation Flow Shop Environments. Complexity 2020, 2020, 1 -17.
AMA StylePablo Valledor, Alberto Gomez, Paolo Priore, Javier Puente. Modelling and Solving Rescheduling Problems in Dynamic Permutation Flow Shop Environments. Complexity. 2020; 2020 ():1-17.
Chicago/Turabian StylePablo Valledor; Alberto Gomez; Paolo Priore; Javier Puente. 2020. "Modelling and Solving Rescheduling Problems in Dynamic Permutation Flow Shop Environments." Complexity 2020, no. : 1-17.
En los últimos años, la moda se ha consolidado como uno de los sectores con mayor volumen de negocio a través de Internet. Sin embargo, algunos estudios indican que los clientes de moda no son fieles a una plataforma concreta. En el presente estudio, mediante la metodología de encuestas a una muestra de 405 clientes de plataforma de venta online en el sector de la moda, se analizan dos dimensiones de la experiencia online (calidad de servicio utilitaria y calidad de servicio hedónica), así como sus efectos directos e indirectos sobre la satisfacción y diversos factores de lealtad (recomendaciones, intención de recompra y tolerancia al precio). La conclusiones obtenidas indican que tanto la calidad utilitaria como la calidad hedónica tienen un impacto similar en la satisfacción, intenciones de recompra y tolerancia al precio. Sin embargo, la calidad hedónica tiene un efecto mayor sobre las recomendaciones (eWOM) de los consumidores que la calidad utilitaria (el doble). Así pues, es relevante potenciar prácticas de gestión de experiencias en las plataformas de venta online que impliquen una eficiente asignación de recursos para conseguir un balance equilibrado entre calidad utilitaria y calidad hedónica.Palabras clave: Moda; calidad e-servicio; satisfacción; lealtad
Adrián Castro-López; Javier Puente; Rodolfo Vázquez-Casielles. ¿Es leal el cliente de moda online? Claves de éxito para maximizar su lealtad en plataformas de venta online. Dirección y Organización 2020, 68 -77.
AMA StyleAdrián Castro-López, Javier Puente, Rodolfo Vázquez-Casielles. ¿Es leal el cliente de moda online? Claves de éxito para maximizar su lealtad en plataformas de venta online. Dirección y Organización. 2020; (70):68-77.
Chicago/Turabian StyleAdrián Castro-López; Javier Puente; Rodolfo Vázquez-Casielles. 2020. "¿Es leal el cliente de moda online? Claves de éxito para maximizar su lealtad en plataformas de venta online." Dirección y Organización , no. 70: 68-77.
This paper proposes the design of a conceptual model of quality assessment in European higher education institutions (HEIs) that takes into account some of the critical reflections made by certain authors in the literature regarding standards and guidelines suggested for this purpose by the European Higher Education Area (EHEA). In addition, the evaluation of the conceptual model was carried out by means of the reliable hybrid methodology MCDM-FIS (multicriteria decision making approach–fuzzy inference system) using FDEMATEL and FDANP methods (fuzzy decision-making trial and evaluation laboratory and FDEMATEL-based analytic network process). The choice of these methodologies was justified by the existing interrelationships among the criteria and dimensions of the model and the degree of subjectivity inherent in its evaluation processes. Finally, it is suggested to include sustainability as a determining factor in the university context due to its great relevance in the training of future professionals.
Javier Puente; Isabel Fernandez; Alberto Gomez; Paolo Priore. Integrating Sustainability in the Quality Assessment of EHEA Institutions: A Hybrid FDEMATEL-ANP-FIS Model. Sustainability 2020, 12, 1707 .
AMA StyleJavier Puente, Isabel Fernandez, Alberto Gomez, Paolo Priore. Integrating Sustainability in the Quality Assessment of EHEA Institutions: A Hybrid FDEMATEL-ANP-FIS Model. Sustainability. 2020; 12 (5):1707.
Chicago/Turabian StyleJavier Puente; Isabel Fernandez; Alberto Gomez; Paolo Priore. 2020. "Integrating Sustainability in the Quality Assessment of EHEA Institutions: A Hybrid FDEMATEL-ANP-FIS Model." Sustainability 12, no. 5: 1707.
We develop a fuzzy evaluation model that provides managers at different responsibility levels in pharmaceutical laboratories with a rich picture of their innovation risk as well as that of competitors. This would help them take better strategic decisions around the management of their present and future portfolio of clinical trials in an uncertain environment. Through three structured fuzzy inference systems (FISs), the model evaluates the overall innovation risk of the laboratories by capturing the financial and pipeline sides of the risk. Three FISs, based on the Mamdani model, determine the level of innovation risk of large pharmaceutical laboratories according to their strategic choices. Two subsystems measure different aspects of innovation risk while the third one builds on the results of the previous two. In all of them, both the partitions of the variables and the rules of the knowledge base are agreed through an innovative 2-tuple-based method. With the aid of experts, we have embedded knowledge into the FIS and later validated the model. In an empirical application of the proposed methodology, we evaluate a sample of 31 large pharmaceutical laboratories in the period 2008-2013. Depending on the relative weight of the two subsystems in the first layer (capturing the financial and the pipeline sides of innovation risk), we estimate the overall risk. Comparisons across laboratories are made and graphical surfaces are analyzed in order to interpret our results. We have also run regressions to better understand the implications of our results. The main contribution of this work is the development of an innovative fuzzy evaluation model that is useful for analyzing the innovation risk characteristics of large pharmaceutical laboratories given their strategic choices. The methodology is valid for carrying out a systematic analysis of the potential for developing new drugs over time and in a stable manner while managing the risks involved. We provide all the necessary tools and datasets to facilitate the replication of our system, which also may be easily applied to other settings.
Javier Puente; Fernando Gascón; Borja Ponte; David de la Fuente. On strategic choices faced by large pharmaceutical laboratories and their effect on innovation risk under fuzzy conditions. Artificial Intelligence in Medicine 2019, 100, 101703 .
AMA StyleJavier Puente, Fernando Gascón, Borja Ponte, David de la Fuente. On strategic choices faced by large pharmaceutical laboratories and their effect on innovation risk under fuzzy conditions. Artificial Intelligence in Medicine. 2019; 100 ():101703.
Chicago/Turabian StyleJavier Puente; Fernando Gascón; Borja Ponte; David de la Fuente. 2019. "On strategic choices faced by large pharmaceutical laboratories and their effect on innovation risk under fuzzy conditions." Artificial Intelligence in Medicine 100, no. : 101703.
The online fashion and textile sector is growing in recent years, becoming one of the online sectors with the highest volume of business. However, the bibliography on e-service quality and its consequences in this sector has been underdeveloped in the last years. This paper presents a model that incorporates the direct and indirect effects of e-service quality (utilitarian and hedonic experience) on satisfaction and loyalty of two segments of customers: transactional and online experimental customers. This research focuses on six online sale platforms, and it has been tested with data on 405 regular customers. The study also develops a model that incorporates the direct and indirect effect of e-service experiences on satisfaction, positive WOM, repurchase intention and price tolerance. The findings indicate that direct and indirect effects of e-service quality on satisfaction and loyalty are different for each segment of customers. While utilitarian quality is more relevant for those customers that only search for information, hedonic quality is especially significant for experiential customers.
Adrian Castro-Lopez; Rodolfo Vazquez-Casielles; Javier Puente. HOW TO MANAGE THE ONLINE EXPERIENCE CONCERNING TRANSACTIONAL AND EXPERIMENTAL CUSTOMERS: CASE OF E-FASHION SECTOR. Journal of Business Economics and Management 2019, 20, 595 -617.
AMA StyleAdrian Castro-Lopez, Rodolfo Vazquez-Casielles, Javier Puente. HOW TO MANAGE THE ONLINE EXPERIENCE CONCERNING TRANSACTIONAL AND EXPERIMENTAL CUSTOMERS: CASE OF E-FASHION SECTOR. Journal of Business Economics and Management. 2019; 20 (3):595-617.
Chicago/Turabian StyleAdrian Castro-Lopez; Rodolfo Vazquez-Casielles; Javier Puente. 2019. "HOW TO MANAGE THE ONLINE EXPERIENCE CONCERNING TRANSACTIONAL AND EXPERIMENTAL CUSTOMERS: CASE OF E-FASHION SECTOR." Journal of Business Economics and Management 20, no. 3: 595-617.
Borja Ena; Javier Puente; Alberto Gomez; Paolo Priore. Auctions in Steel Industry. Proceedings of the Third International Conference on Economic and Business Management (FEBM 2018) 2018, 1 .
AMA StyleBorja Ena, Javier Puente, Alberto Gomez, Paolo Priore. Auctions in Steel Industry. Proceedings of the Third International Conference on Economic and Business Management (FEBM 2018). 2018; ():1.
Chicago/Turabian StyleBorja Ena; Javier Puente; Alberto Gomez; Paolo Priore. 2018. "Auctions in Steel Industry." Proceedings of the Third International Conference on Economic and Business Management (FEBM 2018) , no. : 1.
Dispatching rules are commonly applied to schedule jobs in Flexible Manufacturing Systems (FMSs). However, the suitability of these rules relies heavily on the state of the system; hence, there is no single rule that always outperforms the others. In this scenario, machine learning techniques, such as support vector machines (SVMs), inductive learning-based decision trees (DTs), backpropagation neural networks (BPNs), and case based-reasoning (CBR), offer a powerful approach for dynamic scheduling, as they help managers identify the most appropriate rule in each moment. Nonetheless, different machine learning algorithms may provide different recommendations. In this research, we take the analysis one step further by employing ensemble methods, which are designed to select the most reliable recommendations over time. Specifically, we compare the behaviour of the bagging, boosting, and stacking methods. Building on the aforementioned machine learning algorithms, our results reveal that ensemble methods enhance the dynamic performance of the FMS. Through a simulation study, we show that this new approach results in an improvement of key performance metrics (namely, mean tardiness and mean flow time) over existing dispatching rules and the individual use of each machine learning algorithm.
Paolo Priore; Borja Ponte; Javier Puente; Alberto Gómez. Learning-based scheduling of flexible manufacturing systems using ensemble methods. Computers & Industrial Engineering 2018, 126, 282 -291.
AMA StylePaolo Priore, Borja Ponte, Javier Puente, Alberto Gómez. Learning-based scheduling of flexible manufacturing systems using ensemble methods. Computers & Industrial Engineering. 2018; 126 ():282-291.
Chicago/Turabian StylePaolo Priore; Borja Ponte; Javier Puente; Alberto Gómez. 2018. "Learning-based scheduling of flexible manufacturing systems using ensemble methods." Computers & Industrial Engineering 126, no. : 282-291.
In multi-objective optimisation problems, optimal decisions need to be made in the presence of trade-offs among conflicting objectives which may sometimes be expressed in different units of measure. This makes it difficult to reduce the problem to a single-objective optimisation. Furthermore, when disruptive changes emerge in manufacturing environments, such as the arrival of new jobs or machine breakdowns, the scheduling system should be adapted by responding quickly. In this paper, we propose a rescheduling architecture for solving the problem based on a predictive-reactive strategy and a new method to calculate the reactive schedule in each rescheduling period. Additionally, we developed a methodology that allows the use of multi-objective performance metrics to evaluate dispatching rules. These rules are applied at a benchmark specifically designed for this paper considering three objective functions: makespan, total weighted tardiness and stability. Three types of disruptions are also considered: arrivals of new jobs, machine breakdowns and variations in job processing times. Results showed that the RANDOM rule provides a better behaviour compared to other evaluated rules and a lower ratio of non-dominated solutions compared to ATC (apparent tardiness cost) and FIFO (first-in-first-out) rules. Moreover, the behaviour of the hypervolume metric depends on the problem dimensions.
Pablo Valledor; Alberto Gomez; Paolo Priore; Javier Puente. Solving multi-objective rescheduling problems in dynamic permutation flow shop environments with disruptions. International Journal of Production Research 2018, 56, 6363 -6377.
AMA StylePablo Valledor, Alberto Gomez, Paolo Priore, Javier Puente. Solving multi-objective rescheduling problems in dynamic permutation flow shop environments with disruptions. International Journal of Production Research. 2018; 56 (19):6363-6377.
Chicago/Turabian StylePablo Valledor; Alberto Gomez; Paolo Priore; Javier Puente. 2018. "Solving multi-objective rescheduling problems in dynamic permutation flow shop environments with disruptions." International Journal of Production Research 56, no. 19: 6363-6377.
This paper proposes and validates an e-service quality (eSQ) evaluation model for B2C websites in the textile-and-fashion (TF) sector in Spain. The research allows to represent the positioning of the main websites of this sector according to different utilitarian and hedonic quality dimensions and to establish the global ranking of these websites by using the F-TOPSIS methodology. After a thorough bibliographic review of the most common attributes used to evaluate eSQ of B2C websites, an expert panel has assisted in both, their precise wording and grouping them into the factors and latent dimensions of the proposed model. Later, model validation was carried out through the psychometric analysis of a survey conducted over a sample of 405 users searching/buying on TF industry online sales platforms. The paper already shows the perceptual maps for the eSQ dimensions analyzed for different TF B2C websites. Finally, in order to be able to process the intrinsic uncertainty inherent to the valuations given by the users, the F-TOPSIS method was used to sort the main TF websites. The study has demonstrated the validity of the proposed model, making it replicable in other countries and allowing to obtain the positioning and ranking of the six main websites analyzed in Spain, where Asos and Zara were the leaders.
Adrian Castro Lopez; Javier Puente; Rodolfo Vazquez-Casielles. e-Service Quality Model for Spanish Textile and Fashion Sector: Positioning Analysis and B2C Ranking by F-Topsis. International Journal of Information Technology & Decision Making 2018, 17, 485 -512.
AMA StyleAdrian Castro Lopez, Javier Puente, Rodolfo Vazquez-Casielles. e-Service Quality Model for Spanish Textile and Fashion Sector: Positioning Analysis and B2C Ranking by F-Topsis. International Journal of Information Technology & Decision Making. 2018; 17 (2):485-512.
Chicago/Turabian StyleAdrian Castro Lopez; Javier Puente; Rodolfo Vazquez-Casielles. 2018. "e-Service Quality Model for Spanish Textile and Fashion Sector: Positioning Analysis and B2C Ranking by F-Topsis." International Journal of Information Technology & Decision Making 17, no. 2: 485-512.
This paper designs a bidding and supplier evaluation model focused on strategic product procurement, and develops their respective evaluation knowledge bases. The model is built using the most relevant variables cited in the reviewed procurement literature and allows to compare two evaluation methods: a factor weighting method (WM) and a fuzzy inference system (FIS). By consulting an expert panel and using a two-tuples symbolic translation system, strong fuzzy partitions for all model variables are built. The method, based on central symmetry, permits to obtain the fuzzy label borders from their cores, which have been previously agreed among experts. The system also allows to agree the fuzzy rules to embed in the FIS. The results show the FIS method’s superiority as it allows to better manage the non-linear behavior and the uncertainty inherent to the supplier evaluation process.
Nazario Garcia; Javier Puente; Isabel Fernández; Paolo Priore. Suitability of a Consensual Fuzzy Inference System to Evaluate Suppliers of Strategic Products. Symmetry 2018, 10, 22 .
AMA StyleNazario Garcia, Javier Puente, Isabel Fernández, Paolo Priore. Suitability of a Consensual Fuzzy Inference System to Evaluate Suppliers of Strategic Products. Symmetry. 2018; 10 (1):22.
Chicago/Turabian StyleNazario Garcia; Javier Puente; Isabel Fernández; Paolo Priore. 2018. "Suitability of a Consensual Fuzzy Inference System to Evaluate Suppliers of Strategic Products." Symmetry 10, no. 1: 22.
Adrian Castro-Lopez; Javier Puente; Rodolfo Vazquez-Casielles. Fuzzy inference suitability to determine the utilitarian quality of B2C websites. Applied Soft Computing 2017, 57, 132 -143.
AMA StyleAdrian Castro-Lopez, Javier Puente, Rodolfo Vazquez-Casielles. Fuzzy inference suitability to determine the utilitarian quality of B2C websites. Applied Soft Computing. 2017; 57 ():132-143.
Chicago/Turabian StyleAdrian Castro-Lopez; Javier Puente; Rodolfo Vazquez-Casielles. 2017. "Fuzzy inference suitability to determine the utilitarian quality of B2C websites." Applied Soft Computing 57, no. : 132-143.
Paolo Priore; Raúl Pino; Jose Parreno; Javier Puente; Borja Ponte. Real-Time Scheduling of Flexible Manufacturing Systems Using Support Vector Machines and Case-Based Reasoning. Journal of Economics, Business and Management 2015, 3, 54 -59.
AMA StylePaolo Priore, Raúl Pino, Jose Parreno, Javier Puente, Borja Ponte. Real-Time Scheduling of Flexible Manufacturing Systems Using Support Vector Machines and Case-Based Reasoning. Journal of Economics, Business and Management. 2015; 3 (1):54-59.
Chicago/Turabian StylePaolo Priore; Raúl Pino; Jose Parreno; Javier Puente; Borja Ponte. 2015. "Real-Time Scheduling of Flexible Manufacturing Systems Using Support Vector Machines and Case-Based Reasoning." Journal of Economics, Business and Management 3, no. 1: 54-59.
Nazario Garcia Fernandez; Javier Puente; Isabel Fernandez; Alberto Gomez. CÓMO MEJORAR LA EVALUACIÓN DE PROVEEDORES MEDIANTE SISTEMAS DE INFERENCIA BORROSOS. DYNA 2014, 89, 449 -456.
AMA StyleNazario Garcia Fernandez, Javier Puente, Isabel Fernandez, Alberto Gomez. CÓMO MEJORAR LA EVALUACIÓN DE PROVEEDORES MEDIANTE SISTEMAS DE INFERENCIA BORROSOS. DYNA. 2014; 89 (3):449-456.
Chicago/Turabian StyleNazario Garcia Fernandez; Javier Puente; Isabel Fernandez; Alberto Gomez. 2014. "CÓMO MEJORAR LA EVALUACIÓN DE PROVEEDORES MEDIANTE SISTEMAS DE INFERENCIA BORROSOS." DYNA 89, no. 3: 449-456.
Nazario García; Javier Puente; Isabel Fernández; Paolo Priore. Supplier selection model for commodities procurement. Optimised assessment using a fuzzy decision support system. Applied Soft Computing 2013, 13, 1939 -1951.
AMA StyleNazario García, Javier Puente, Isabel Fernández, Paolo Priore. Supplier selection model for commodities procurement. Optimised assessment using a fuzzy decision support system. Applied Soft Computing. 2013; 13 (4):1939-1951.
Chicago/Turabian StyleNazario García; Javier Puente; Isabel Fernández; Paolo Priore. 2013. "Supplier selection model for commodities procurement. Optimised assessment using a fuzzy decision support system." Applied Soft Computing 13, no. 4: 1939-1951.
Rafael Rosillo; Javier Giner; Javier Puente; Borja Ponte. Different Stock Market Models Using Support Vector Machines. International Journal of Trade, Economics and Finance 2013, 310 -313.
AMA StyleRafael Rosillo, Javier Giner, Javier Puente, Borja Ponte. Different Stock Market Models Using Support Vector Machines. International Journal of Trade, Economics and Finance. 2013; ():310-313.
Chicago/Turabian StyleRafael Rosillo; Javier Giner; Javier Puente; Borja Ponte. 2013. "Different Stock Market Models Using Support Vector Machines." International Journal of Trade, Economics and Finance , no. : 310-313.
The aim of this paper is to develop a methodology that is useful for analysing from a microeconomic perspective the incentives to entry, permanence and exit in the market for pharmaceutical generics under fuzzy conditions. In an empirical application of our proposed methodology, the potential towards permanence of labs with different characteristics has been estimated. The case we deal with is set in an open market where global players diversify into different national markets of pharmaceutical generics. Risk issues are significantly important in deterring decision makers from expanding in the generic pharmaceutical business. However, not all players are affected in the same way and/or to the same extent. Small, non-diversified generics labs are in the worse position. We have highlighted that the expected NPV and the number of generics in the portfolio of a pharmaceutical lab are important variables, but that it is also important to consider the degree of diversification. Labs with a higher potential for diversification across markets have an advantage over smaller labs. We have described a fuzzy decision support system based on the Mamdani model in order to determine the incentives for a laboratory to remain in the market both when it is stable and when it is growing.
Javier Puente; David De La Fuente; Jesús Lozano; Fernando Gascón. On firm specific characteristics of pharmaceutical generics and incentives to permanence under fuzzy conditions. 2012, 1 .
AMA StyleJavier Puente, David De La Fuente, Jesús Lozano, Fernando Gascón. On firm specific characteristics of pharmaceutical generics and incentives to permanence under fuzzy conditions. . 2012; ():1.
Chicago/Turabian StyleJavier Puente; David De La Fuente; Jesús Lozano; Fernando Gascón. 2012. "On firm specific characteristics of pharmaceutical generics and incentives to permanence under fuzzy conditions." , no. : 1.
Dispatching rules are usually applied to dynamically schedule jobs in flexible manufacturing systems (FMSs). Despite their frequent use a significant drawback is that the performance level of the rule is dictated by the current state of the manufacturing system. Because no rule is better than any other for every system state, it would be highly desirable to know which rule is the most appropriate for each given condition. To achieve this goal we propose a scheduling approach using support vector machines (SVMs). By using this technique and by analyzing the earlier performance of the system, “scheduling knowledge” is obtained whereby the right dispatching rule at each particular moment can be determined. Simulation results show that the proposed approach leads to significant performance improvements over existing dispatching rules. In the same way it is also confirmed that SVMs perform better than other traditional machine learning algorithms as the inductive learning when applied to FMS scheduling problem, due to their better generalization capability.
Paolo Priore; Jose Parreno; Raul Pino; Alberto Gomez; Javier Puente. LEARNING-BASED SCHEDULING OF FLEXIBLE MANUFACTURING SYSTEMS USING SUPPORT VECTOR MACHINES. Applied Artificial Intelligence 2010, 24, 194 -209.
AMA StylePaolo Priore, Jose Parreno, Raul Pino, Alberto Gomez, Javier Puente. LEARNING-BASED SCHEDULING OF FLEXIBLE MANUFACTURING SYSTEMS USING SUPPORT VECTOR MACHINES. Applied Artificial Intelligence. 2010; 24 (3):194-209.
Chicago/Turabian StylePaolo Priore; Jose Parreno; Raul Pino; Alberto Gomez; Javier Puente. 2010. "LEARNING-BASED SCHEDULING OF FLEXIBLE MANUFACTURING SYSTEMS USING SUPPORT VECTOR MACHINES." Applied Artificial Intelligence 24, no. 3: 194-209.
According to Bologna's Declaration and consequent introduction of the European Space of Higher Education, virtual educational tools implementation is an almost mandatory task for every University around Europe. Since 1999, Spain's University of Oviedo has been developing a virtual education tool called 'Virtual Campus' to help professors to undertake a new and more modern way of teaching and interacting with students. Implanting a subject in University of Oviedo's 'Virtual Campus' entails a continuous monitoring by the professor of the students performance, as well as adding educational materials to be used by students. In this paper, the design and implementation of the subject 'Operations Management' in 'Virtual Campus' is addressed. This subject belongs to the fourth year of the Industrial Engineering studies in the University of Oviedo at Gijon. Besides presenting the design and implementation of this subject in 'Virtual Campus', the design, results and conclusions of a survey in which the students had the chance to share their experiences with the use of this virtual educational tool are presented in this work.
Jose Parreno; Javier Puente; Patricia Ordonez De Pablos; Paolo Priore. Implementation of the subject 'Operations Management' on the University of Oviedo's virtual education tool 'Virtual Campus'. International Journal of Teaching and Case Studies 2009, 2, 181 .
AMA StyleJose Parreno, Javier Puente, Patricia Ordonez De Pablos, Paolo Priore. Implementation of the subject 'Operations Management' on the University of Oviedo's virtual education tool 'Virtual Campus'. International Journal of Teaching and Case Studies. 2009; 2 (2):181.
Chicago/Turabian StyleJose Parreno; Javier Puente; Patricia Ordonez De Pablos; Paolo Priore. 2009. "Implementation of the subject 'Operations Management' on the University of Oviedo's virtual education tool 'Virtual Campus'." International Journal of Teaching and Case Studies 2, no. 2: 181.
Organising shifts, or work rosters, is a problem that affects a large number of businesses where employees are subject to some kind of work rotation. Researchers in the fields of Operations Research and Artificial Intelligence have resorted to several different optimisation systems to solve the problem. The motivation for the medical-staff shift-rotation research presented in this paper stems from the needs of an actual hospital emergency department (HED) and from the observed growing staff of these services in Spain. The problem approach, which has been hardly dealt with in the literature, intends to automate the creation of time-tables by applying genetic algorithms (GAs) in an actual HED. HEDs work organisation becomes different because of the combination of shifts and 24-h duties. After knowing the HED workers’ requirements (which will allow to identify the hard and soft constraints imposed to the problem) and after defining the adequate encoding to be used in the solutions, a heuristic-schedule builder –designed ad hoc to satisfy the hard constraints – produces an initial population of feasible solutions. Afterwards, iteratively, GA obtains new generations of feasible individuals, thanks to the use of a specific crossover operator, based in the exchange of whole work weeks, that operates together with a repair function. Once the optimum is reached, the results obtained are discussed as a function of the degree of satisfaction of the constraints under which the system operates and of the adaptability of the system as the constraints vary.
Javier Puente; Alberto Gómez; Isabel Fernández; Paolo Priore. Medical doctor rostering problem in a hospital emergency department by means of genetic algorithms. Computers & Industrial Engineering 2008, 56, 1232 -1242.
AMA StyleJavier Puente, Alberto Gómez, Isabel Fernández, Paolo Priore. Medical doctor rostering problem in a hospital emergency department by means of genetic algorithms. Computers & Industrial Engineering. 2008; 56 (4):1232-1242.
Chicago/Turabian StyleJavier Puente; Alberto Gómez; Isabel Fernández; Paolo Priore. 2008. "Medical doctor rostering problem in a hospital emergency department by means of genetic algorithms." Computers & Industrial Engineering 56, no. 4: 1232-1242.
The considerable amount of uncertainty involved in defining the factors that affect reverse logistics (RL) decision-making and the complex interrelationships between those factors make it rather difficult to decide what recovery policy a business should pursue. This article proposes a fuzzy system that helps in such decision-making and thereby mitigates these difficulties. The knowledge related to the decision is incorporated into the system by means of conditional rules, which serve to provide the ideal recovery policy for each particular case. The model proposed is applied to the analysis of a number of examples and proves to be a versatile tool that provides coherent results. These characteristics could be of critical importance especially in the point of entry into the RL pipeline and in the centralized return centres.
Isabel Fernandez; Javier Puente; Nazario Garcia; Alberto Gomez. A Decision-Making Support System on a Products Recovery Management Framework. A Fuzzy Approach. Concurrent Engineering 2008, 16, 129 -138.
AMA StyleIsabel Fernandez, Javier Puente, Nazario Garcia, Alberto Gomez. A Decision-Making Support System on a Products Recovery Management Framework. A Fuzzy Approach. Concurrent Engineering. 2008; 16 (2):129-138.
Chicago/Turabian StyleIsabel Fernandez; Javier Puente; Nazario Garcia; Alberto Gomez. 2008. "A Decision-Making Support System on a Products Recovery Management Framework. A Fuzzy Approach." Concurrent Engineering 16, no. 2: 129-138.