Towards interoperability through inter-enterprise collaboration architectures

Most enterprise architectures published so far are capable of generating reasonably good descriptive models for individual enterprises to enable integration, organization and synchronization of enterprise elements: organizational structure, business processes, information systems and technology infrastructure, among others. However, research in this field applied to the extended enterprise or inter-enterprise architectures that takes into account the growing trend towards complex collaborative environments is very scarce. In this sense, this article seeks to analyze, link and synthesize the researches that has addressed the disciplines of enterprise architecture and business collaboration, in order to identify possible future research needs from the conceptualization made.Vargas, A.; Boza Garcia, A.; Cuenca, L. (2011). Towards interoperability through inter-enterprise collaboration architectures. En On the Move to Meaningful Internet Systems: OTM 2011 Workshops. Springer Verlag (Germany). 7046:102-111. doi:10.1007/978-3-642-25126-9_18S1021117046Adam, O., Hofer, A., Zang, S., Hammer, C., Jerrentrup, M., Leinenbach, S.: A Collaboration Framework for Cross-enterprise Business Process Management. In: First International Conference on Interoperability of Enterprise Software and Application, Geneva (2005)Chalmeta, R., Grangel, R.: ARDIN extension for virtual enterprise integration. The Journal of Systems and Software 67, 141–152 (2003)Choi, Y., Kang, D., Chae, H., Kim, K.: An enterprise architecture framework for collaboration of virtual enterprise chains. The International Journal of Advanced Manufacturing Technology 35, 1065–1078 (2008)Schekkerman, J.: Extended Enterprise Architecture Framework Essentials Guide. Institute For Enterprise Architecture Developments, IFEAD (2006), http://www.enterprise-architecture.info/index.htmISO 15704. Industrial automation systems - Requirements for enterprise-reference architectures and methodologies.: International Organization for Standardization (2000)Kosanke, K., Vernadat, F., Zelm, M.: CIMOSA: Enterprise engineering and integration. Computers in Industry 40, 83–97 (1999)Cuenca, L.: Marco arquitectónico para la propuesta IE-GIP. Extensión de la arquitectura CIMOSA. Aplicación a una empresa del sector cerámico. PhD thesis. Universidad Politécnica de ValenciaMolina, A., Panetto, H., Chen, D., Whitman, L.: Enterprise Integration and Networking: challenges and trends. Studies in Informatics and Control 16(4), 353–368 (2007)Ortiz, A., Lario, F., Ros, L.: Enterprise Integration—Business Processes Integrated Management: a proposal for a methodology to develop Enterprise Integration Programs. Computers in Industry 40, 155–171 (1999)Chalmeta, R., Campos, C., Grangel, R.: References architectures for enterprise integration. The Journal of Systems and Software 57, 175–191 (2001)Vernadat, F.: Enterprise modeling and integration (EMI): Current status and research perspectives. Annual Reviews in Control 26, 15–25 (2002)Williams, T., Li, H.: PERA and GERAM enterprise reference architectures in enterprise integration. Information Infrastructure Systems for Manufacturing, 1–27 (1998)Lankhorst, M.: Enterprise Architecture at Work: Modelling, Communication and Analysis. Springer, Heidelberg (2009)Arango, M., Londoño, J., Zapata, J.: Arquitectura empresarial- Una visión general. Revista Ingenierías Universidad de Medellín 9(16), 101–111 (2010)Bernard, S.: An introduction to enterprise architecture. AuthorHouse, Bloomington (2005)Cuenca, L., Ortiz, A., Boza, A.: Arquitectura de Empresa. Visión General. In: IX Congreso de Ingeniería de Organización, Gijón (2005)Maya, E.: Arquitectura empresarial: un nuevo reto para las empresas de hoy. Centro de Investigación de las Telecomunicaciones. INTERACTIC: Interacción con la información (2010), http://www.interactic.org.co/THE OPEN GROUP.: ARCHIMATE, The Power of Enterprise Architecture (2009), http://www.archimate.org/en/home/Stelzer, D.: Enterprise Architecture Principles: Literature Review and Research Directions. In: Dan, A., Gittler, F., Toumani, F. (eds.) ICSOC/ServiceWave 2009. LNCS, vol. 6275, pp. 12–21. Springer, Heidelberg (2010)Schekkerman, J.: Enterprise architecture validation. Achieving business-aligned and validated enterprise architectures. Institute For Enterprise Architecture Developments, IFEAD (2004), http://www.enterprise-architecture.info/index.htmKosanke, K.: CIMOSA Primer on key concepts, purpose and business value (1996), http://cimosa.cnt.pl/Chen, D., Vallespir, B., Doumeingts, G.: GRAI integrated methodology and its mapping onto generic enterprise reference architecture and methodology. Computers in Industry 33, 387–394 (1997)Rathwell, G.: PERA Enterprise Integration Web Site (2005), http://www.pera.net/Williams, T., Rathwell, G., Li, H.: A handbook on master planning and implementation for enterprise integration programs. PERA Enterprise Integration Web Site (2001), http://www.pera.net/IFIP.: GERAM: Generalised Enterprise Reference Architecture and Methodology. International Federation for Information Processing (1999), http://dl.ifip.org/index.php/index/indexOrtiz, A.: Propuesta para el Desarrollo de Programas de Integración Empresarial en Empresas Industriales. Aplicación a una Empresa del Sector Cerámico. Universidad Politécnica de Valencia (1998)Cuenca, L., Boza, A., Ortiz, A.: Architecting business and IS/IT strategic alignment for extend enterprises. Studies in Informatics and Control 20(1), 7–18 (2011)The Open Group (2011), https://www.opengroup.org/index.htmGrangel, R.: Propuesta para el Modelado del Conocimiento Empresarial. PhD thesis Universidad Jaume I de Castello (2007)Scheer, A., Schneider, K.: ARIS – Architecture of Integrated Information. Handbook on Architectures of Information Systems. International Handbooks on Information Systems 3, 605–623 (2006)ISO/CEN 19439. Enterprise integration - Framework for enterprise modelling.: International Organization for Standardization (2006)Stadtler, H., Kilger, C.: Supply Chain Management and advance planning. Concepts, Models, Sofware and Cases Studies. Springer, Heidelberg (2002)Alarcón, F., Ortiz, A., Alemany, M., Lario, F.: Planificación Colaborativa en un contexto de varias Cadenas de Suministro: ventajas y desventajas. In: VIII Congreso de Ingeniería de Organización, Leganés, pp. 857–866 (2004)Alarcón, F.: Desarrollo de una Arquitectura para la definición del proceso de Comprometer Pedidos en contextos de Redes de Suministro Colaborativas. Aplicación a una Red compuesta por Cadenas de Suministro en los Sectores Cerámico y del Mueble. PhD thesis Universidad Politécnica de Valencia (2005)Petersen, K., Ragatz, G., Monczka, R.: An Examination of Collaborative Planning Effectiveness and Supply Chain Performance. The Journal of Supply Chain Management 41(2), 14–25 (2005)Ribas, I., Companys, R.: Estado del arte de la planificación colaborativa en la cadena de suministro: Contexto determinista e incierto. Intangible Capital, 91–121 (2007)Ribas, I., Lario, F., Companys, R.: Modelos para la planificación colaborativa en la cadena de suministro: contexto determinista e incierto. In: Congreso de ingeniería de organización, Valencia, pp. 1–10 (2006)Dudek, G.: Collaborative Planning in Supply Chains. Supply Chain Management and Collaborative Planning. Springer, Heidelberg (2009)Stadtler, H.: A framework for collaborative planning and state-of-the-art. OR Spectrum 31, 5–30 (2009)Kilger, C., Reuter, B., Stadtler, H.: Collaborative Planning. In: Stadtler, H., Kilger, C. (eds.) Supply Chain Management and Advanced Planning-—Concepts, Models Software and Case Studies, pp. 263–284. Springer, Heidelberg (2008)Audy, J., Lehoux, N., D’Amours, S.: A framework for an efficient implementation of logistics collaborations. International Transactions in Operational Research, 1–25 (2010)Zachman, J.: A Framework for Information Systems Architecture. IBM Systems Journal 26(3), 454–470 (1987

On the equivalence of strong formulations for capacitated multi-level lot sizing problems with setup times

Several mixed integer programming formulations have been proposed for modeling capacitated multi-level lot sizing problems with setup times. These formulations include the so-called facility location formulation, the shortest route formulation, and the inventory and lot sizing formulation with (l,S) inequalities. In this paper, we demonstrate the equivalence of these formulations when the integrality requirement is relaxed for any subset of binary setup decision variables. This equivalence has significant implications for decomposition-based methods since same optimal solution values are obtained no matter which formulation is used. In particular, we discuss the relax-and-fix method, a decomposition-based heuristic used for the efficient solution of hard lot sizing problems. Computational tests allow us to compare the effectiveness of different formulations using benchmark problems. The choice of formulation directly affects the required computational effort, and our results therefore provide guidelines on choosing an effective formulation during the development of heuristic-based solution procedures

Temperature forecasting by deep learning methods

Numerical weather prediction (NWP) models solve a system of partial differential equations based on physical laws to forecast the future state of the atmosphere. These models are deployed operationally, but they are computationally very expensive. Recently, the potential of deep neural networks to generate bespoke weather forecasts has been explored in a couple of scientific studies inspired by the success of video frame prediction models in computer vision. In this study, a simple recurrent neural network with convolutional filters, called ConvLSTM, and an advanced generative network, the Stochastic Adversarial Video Prediction (SAVP) model, are applied to create hourly forecasts of the 2 m temperature for the next 12 h over Europe. We make use of 13 years of data from the ERA5 reanalysis, of which 11 years are utilized for training and 1 year each is used for validating and testing. We choose the 2 m temperature, total cloud cover, and the 850 hPa temperature as predictors and show that both models attain predictive skill by outperforming persistence forecasts. SAVP is superior to ConvLSTM in terms of several evaluation metrics, confirming previous results from computer vision that larger, more complex networks are better suited to learn complex features and to generate better predictions. The 12 h forecasts of SAVP attain a mean squared error (MSE) of about 2.3 K2, an anomaly correlation coefficient (ACC) larger than 0.85, a structural similarity index (SSIM) of around 0.72, and a gradient ratio (rG) of about 0.82. The ConvLSTM yields a higher MSE (3.6 K2), a smaller ACC (0.80) and SSIM (0.65), and a slightly larger rG (0.84). The superior performance of SAVP in terms of MSE, ACC, and SSIM can be largely attributed to the generator. A sensitivity study shows that a larger weight of the generative adversarial network (GAN) component in the SAVP loss leads to even better preservation of spatial variability at the cost of a somewhat increased MSE (2.5 K2). Including the 850 hPa temperature as an additional predictor enhances the forecast quality, and the model also benefits from a larger spatial domain. By contrast, adding the total cloud cover as predictor or reducing the amount of training data to 8 years has only small effects. Although the temperature forecasts obtained in this way are still less powerful than contemporary NWP models, this study demonstrates that sophisticated deep neural networks may achieve considerable forecast quality beyond the nowcasting range in a purely data-driven way.</p

Model of optimization of mining complex for the planning of flow of quarry production of limestone in multiple products and with elements for the analysis of the capacity

Activities in mining complexes contain multiple decisions that affect the operations of the system for the extraction, transformation, transport and storage of various subsoil components. The purpose of this research is the planning of continuous flow production systems for mixed products, in non-metallic mining extraction processes, considering bottlenecks and capacity planning. This paper presents a model for production, based on mathematical optimization, that facilitates the planning and management of operations in the area of extraction, crushing and transformation of a quarry of aggregates for construction, considering the resources and the constraints that allow to define effective strategies in the increase of the productivity of the lines of low production environment by scenarios. This research develops an analysis of bottlenecks and contrasts the nature of the production system by means of a mathematical model of optimization, which considers the capacities and balances in the flows of the Limestone production line. The mathematical model that maximizes profits can be adapted to systems of continuous flow production in mining complexes where their products are part of a reverse logistics process, analysis of alternatives of extraction, transformation and transport

Mixed integer programming in production planning with backlogging and setup carryover : modeling and algorithms

This paper proposes a mixed integer programming formulation for modeling the capacitated multi-level lot sizing problem with both backlogging and setup carryover. Based on the model formulation, a progressive time-oriented decomposition heuristic framework is then proposed, where improvement and construction heuristics are effectively combined, therefore efficiently avoiding the weaknesses associated with the one-time decisions made by other classical time-oriented decomposition algorithms. Computational results show that the proposed optimization framework provides competitive solutions within a reasonable time

A computational analysis of lower bounds for big bucket production planning problems

In this paper, we analyze a variety of approaches to obtain lower bounds for multi-level production planning problems with big bucket capacities, i.e., problems in which multiple items compete for the same resources. We give an extensive survey of both known and new methods, and also establish relationships between some of these methods that, to our knowledge, have not been presented before. As will be highlighted, understanding the substructures of difficult problems provide crucial insights on why these problems are hard to solve, and this is addressed by a thorough analysis in the paper. We conclude with computational results on a variety of widely used test sets, and a discussion of future research