Who Risks and Wins? - Simulated Cost Variance in Sustainable Construction Projects

[EN] More and more construction projects are closed before they ever start. Among the most significant reasons for project failures is cost risk. Construction companies have many problems with reliable cost management. Rising demands of the key market players insist on making construction projects more sustainable according to the simultaneous improvement of the economic, environmental and social responsiveness dimensions. In order to investigate these problems, a four-phase research methodology has been followed consisting of: (1) literature review to identify research trends and gaps, (2) survey to construction experts to detect their subjective perspectives about risk costs and analyse the corresponding costs structure for the investment in sustainable projects, (3) simulations based on Monte Carlo simulation with an author's methodology for calculating the cost risk with an additional statistical analysis, (4) ending questionnaire to obtain the final feedback from the experts and the validation of obtained results. A contribution to the development of knowledge about cost risk is the observation that the changing probability distributions of individual cost-generating components may include both economic as well as technological and organizational aspects. Thus, with the proposed approach, often complex, global challenges of sustainable construction projects can be tackled in an accessible way.Statutory research at the UTP University of Science and Technology, Bydgoszcz, Poland.Górecki, J.; Díaz-Madroñero Boluda, FM. (2020). Who Risks and Wins? - Simulated Cost Variance in Sustainable Construction Projects. Sustainability. 12(8):1-31. https://doi.org/10.3390/su12083370S131128Wong, J. M. W., Thomas Ng, S., & Chan, A. P. C. (2010). Strategic planning for the sustainable development of the construction industry in Hong Kong. Habitat International, 34(2), 256-263. doi:10.1016/j.habitatint.2009.10.002Sobotka, A. (2017). Innovative solutions in engineering of construction projects. Procedia Engineering, 208, 160-165. doi:10.1016/j.proeng.2017.11.034Kaplinski, O. (2013). Risk Management of Construction Works by Means of the Utility Theory: A Case Study. Procedia Engineering, 57, 533-539. doi:10.1016/j.proeng.2013.04.068Diekmann, J. 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MRP IV: Planificación de requerimientos de materiales cuarta generación. Integración de la planificación de la producción y del transporte de aprovisionamiento

Tesis por compendioEl sistema de planificación de requerimientos de materiales o MRP (Material Requirement Planning), desarrollado por Orlicky en 1975, sigue siendo en nuestros días y, a pesar de sus deficiencias identificadas, el sistema de planificación de la producción más utilizado por las empresas industriales. Las evoluciones del MRP se vieron reflejadas en el sistema MRPII (Manufacturing Resource Planning), que considera restricciones de capacidad productiva, MRPIII (Money Resource Planning), que introduce la función de finanzas; y la evolución comercial del mismo en el ERP (Enterprise Resource Planning), que incorpora modularmente todas las funciones de la empresa en un único sistema de decisión, cuyo núcleo central es el MRP. Los desarrollos posteriores de los sistemas ERP han incorporado las nuevas tecnologías de la información y comunicaciones. Asimismo, éstos se han adaptado al contexto económico actual caracterizado por la globalización de los negocios y la deslocalización de los proveedores desarrollando otras funciones como la gestión de la cadena de suministro o del transporte, entre otros. Por otro lado, existen muchos trabajos en la literatura académica que han intentado resolver algunas de las debilidades del MRP tales como la optimización de los resultados, la consideración de la incertidumbre en determinados parámetros, el inflado de los tiempos de entrega, etc. Sin embargo, tanto en el ámbito comercial como en el científico, el MRP y sus variantes se centran en el requerimiento de los materiales y en la planificación de las capacidades de producción, lo que es su desventaja principal en aquellas cadenas de suministro donde existe una gran deslocalización de los proveedores de materias primas y componentes. En estos entornos, la planificación del transporte adquiere un protagonismo fundamental, puesto que los elevados costes y las restricciones logísticas suelen hacer subóptimos e incluso infactibles los planes de producción propuestos, siendo la re-planificación manual una práctica habitual en las empresas. Esta tesis doctoral propone un modelo denominado MRPIV, que considera de forma integrada las decisiones de la planificación de materiales, capacidades de recursos de producción y el transporte, con las restricciones propias de este último, tales como diferentes modos de recogida (milk-run, camión completo, rutas) en la cadena de suministro con el objetivo de evitar la suboptimización de estos planes que en la actualidad se generan usualmente de forma secuencial e independiente. El modelo propuesto se ha validado en una cadena de suministro del sector del automóvil confirmando la reducción de costes totales y una planificación más eficiente del transporte de los camiones necesarios para efectuar el aprovisionamiento.Díaz-Madroñero Boluda, FM. (2015). MRP IV: Planificación de requerimientos de materiales cuarta generación. Integración de la planificación de la producción y del transporte de aprovisionamiento [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/48524TESISCompendi

Architecture for collaborative planning, forecasting and replenishment in a mass customization environment

[EN] In this paper, an architecture for collaborative planning, forecasting and replenishment in a mass customization environment is proposed. For this, on one hand, the main activities of the most important collaborative models and, on the other hand, the main processes related to mass customization environments. In order to achieve it, a set of interfaces are proposed, associated with the definition of products and additional services, the manufacturing and shipping of products, as well as transport and reception. The proposal is composed of a conceptual model, an implementation methodology, as well as possible technological solutions for its development in industrial companies[ES] En este trabajo se propone una arquitectura para la previsión, planificación y reaprovisionamiento colaborativo en un entorno de personalización en masa. Para ello, se identifica las actividades principales de los modelos colaborativos más destacados y los procesos principales asociados a los entornos de personalización en masa. Para llegar a ésta, se proponen un conjunto de interfases asociados a la definición de productos y servicios adicionales, a la fabricación y expedición, así como a actividades de transporte y recepción. La propuesta se compone de un modelo conceptual, una metodología de implantación, así como por posibles soluciones tecnológicas asociadas para su desarrollo en empresas industriales.Díaz-Madroñero Boluda, FM.; Poler, R. (2017). Arquitectura para la previsión, planificación y reaprovisionamiento colaborativo en un entorno de personalización en masa. Direccion y Organizacion. (63):5-20. http://hdl.handle.net/10251/108649S5206

Tools for managing references in class projects and scientific works

[EN] This paper presents a set of tools to manage references, for its application in class projects, in the university context, and in scientific works. The main aim of this paper is to provide a set of tools to support university students and researchers to store all their research, and sort all their references, documents and notes in one place. This paper is an extension of the paper Adjustment of students to be future researchers: The importance of a systematic literature review methodology for MSC students [1] that proposes a guideline to help students to systematically perform the literature review phase in the research work. The work developed in the present paper, focuses on collecting, managing and treating the results through building a personalised database, proposing in a more extended way a set of tools to manage references of the research work performed in the systematic literature review.The research leading to these results has received funding from European Community's H2020 Programme (H2020/2014-2020) under grant agreement no 636909, "Cloud Collaborative Manufacturing Networks (C2NET)".Andres, B.; Poler, R.; Díaz-Madroñero Boluda, FM. (2017). Tools for managing references in class projects and scientific works. INTED proceedings (Online). 210-219. https://doi.org/10.21125/inted.2017.0172S21021

Fuzzy goal programming for material requirements planning under uncertainty and integrity conditions

"This is an Accepted Manuscript of an article published in International Journal of Production Research on December 2014, available online: http://www.tandfonline.com/10.1080/00207543.2014.920115."In this paper, we formulate the material requirements planning) problem of a first-tier supplier in an automobile supply chain through a fuzzy multi-objective decision model, which considers three conflictive objectives to optimise: minimisation of normal, overtime and subcontracted production costs of finished goods plus the inventory costs of finished goods, raw materials and components; minimisation of idle time; minimisation of backorder quantities. Lack of knowledge or epistemic uncertainty is considered in the demand, available and required capacity data. Integrity conditions for the main decision variables of the problem are also considered. For the solution methodology, we use a fuzzy goal programming approach where the importance of the relations among the goals is considered fuzzy instead of using a crisp definition of goal weights. For illustration purposes, an example based on modifications of real-world industrial problems is used.This work has been funded by the Universitat Politecnica de Valencia Project: 'Material Requirements Planning Fourth Generation (MRPIV)' (Ref. PAID-05-12).Díaz-Madroñero Boluda, FM.; Mula, J.; Jiménez, M. (2014). Fuzzy goal programming for material requirements planning under uncertainty and integrity conditions. International Journal of Production Research. 52(23):6971-6988. doi:10.1080/00207543.2014.920115S697169885223Aköz, O., & Petrovic, D. (2007). A fuzzy goal programming method with imprecise goal hierarchy. European Journal of Operational Research, 181(3), 1427-1433. doi:10.1016/j.ejor.2005.11.049Alfieri, A., & Matta, A. (2010). 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Fuzzy Sets and Systems, 157(10), 1328-1332. doi:10.1016/j.fss.2005.12.003Louly, M.-A., & Dolgui, A. (2011). Optimal time phasing and periodicity for MRP with POQ policy. International Journal of Production Economics, 131(1), 76-86. doi:10.1016/j.ijpe.2010.04.042Louly, M. A., Dolgui, A., & Hnaien, F. (2008). Optimal supply planning in MRP environments for assembly systems with random component procurement times. International Journal of Production Research, 46(19), 5441-5467. doi:10.1080/00207540802273827Mohapatra, P., Benyoucef, L., & Tiwari, M. K. (2013). Integration of process planning and scheduling through adaptive setup planning: a multi-objective approach. International Journal of Production Research, 51(23-24), 7190-7208. doi:10.1080/00207543.2013.853890Mula, J., & Díaz-Madroñero, M. (2012). Solution Approaches for Material Requirement Planning* with Fuzzy Costs. 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Overview of Dynamic Facility Layout Planning as a Sustainability Strategy

[EN] The facility layout design problem is significantly relevant within the business operations strategies framework and has emerged as an alternate strategy towards supply chain sustainability. However, its wide coverage in the scientific literature has focused mainly on the static planning approach and disregarded the dynamic approach, which is very useful in real-world applications. In this context, the present article offers a literature review of the dynamic facility layout problem (DFLP). First, a taxonomy of the reviewed papers is proposed based on the problem formulation current trends (related to the problem type, planning phase, planning approach, number of facilities, number of floors, number of departments, space consideration, department shape, department dimensions, department area, and materials handling configuration); the mathematical modeling approach (regarding the type of model, type of objective function, type of constraints, nature of market demand, type of data, and distance metric), and the considered solution approach. Then, the extent to which recent research into DFLP has contributed to supply chain sustainability by addressing its three performance dimensions (economic, environmental, social) is described. Finally, some future research guidelines are provided.This research was funded by the Spanish Ministry of Science, Innovation and Universities Project CADS4.0, grant number RTI2018-101344-B-I00; and the Valencian Community ERDF Programme 2014-2020, grant number IDIFEDER/2018/025.Pérez-Gosende, P.; Mula, J.; Díaz-Madroñero Boluda, FM. (2020). Overview of Dynamic Facility Layout Planning as a Sustainability Strategy. Sustainability. 12(19):1-16. https://doi.org/10.3390/su12198277S1161219Ghassemi Tari, F., & Neghabi, H. (2015). A new linear adjacency approach for facility layout problem with unequal area departments. Journal of Manufacturing Systems, 37, 93-103. doi:10.1016/j.jmsy.2015.09.003Kheirkhah, A., Navidi, H., & Messi Bidgoli, M. (2015). Dynamic Facility Layout Problem: A New Bilevel Formulation and Some Metaheuristic Solution Methods. IEEE Transactions on Engineering Management, 62(3), 396-410. doi:10.1109/tem.2015.2437195Altuntas, S., & Selim, H. (2012). Facility layout using weighted association rule-based data mining algorithms: Evaluation with simulation. Expert Systems with Applications, 39(1), 3-13. doi:10.1016/j.eswa.2011.06.045Ku, M.-Y., Hu, M. H., & Wang, M.-J. (2011). Simulated annealing based parallel genetic algorithm for facility layout problem. International Journal of Production Research, 49(6), 1801-1812. doi:10.1080/00207541003645789Navidi, H., Bashiri, M., & Messi Bidgoli, M. (2012). A heuristic approach on the facility layout problem based on game theory. International Journal of Production Research, 50(6), 1512-1527. doi:10.1080/00207543.2010.550638Hosseini-Nasab, H., Fereidouni, S., Fatemi Ghomi, S. M. T., & Fakhrzad, M. B. (2017). Classification of facility layout problems: a review study. The International Journal of Advanced Manufacturing Technology, 94(1-4), 957-977. doi:10.1007/s00170-017-0895-8Carter, C. R., & Rogers, D. S. (2008). A framework of sustainable supply chain management: moving toward new theory. International Journal of Physical Distribution & Logistics Management, 38(5), 360-387. doi:10.1108/09600030810882816Carter, C. R., & Washispack, S. (2018). Mapping the Path Forward for Sustainable Supply Chain Management: A Review of Reviews. Journal of Business Logistics, 39(4), 242-247. doi:10.1111/jbl.12196Roy, V., Schoenherr, T., & Charan, P. (2018). The thematic landscape of literature in sustainable supply chain management (SSCM). International Journal of Operations & Production Management, 38(4), 1091-1124. doi:10.1108/ijopm-05-2017-0260Barbosa-Póvoa, A. P., da Silva, C., & Carvalho, A. (2018). Opportunities and challenges in sustainable supply chain: An operations research perspective. European Journal of Operational Research, 268(2), 399-431. doi:10.1016/j.ejor.2017.10.036Tonelli, F., Evans, S., & Taticchi, P. (2013). Industrial sustainability: challenges, perspectives, actions. International Journal of Business Innovation and Research, 7(2), 143. doi:10.1504/ijbir.2013.052576Sánchez-Flores, R. B., Cruz-Sotelo, S. E., Ojeda-Benitez, S., & Ramírez-Barreto, M. E. (2020). Sustainable Supply Chain Management—A Literature Review on Emerging Economies. Sustainability, 12(17), 6972. doi:10.3390/su12176972Ford, S., & Despeisse, M. (2016). Additive manufacturing and sustainability: an exploratory study of the advantages and challenges. Journal of Cleaner Production, 137, 1573-1587. doi:10.1016/j.jclepro.2016.04.150Kamble, S. S., Gunasekaran, A., & Gawankar, S. A. (2018). Sustainable Industry 4.0 framework: A systematic literature review identifying the current trends and future perspectives. Process Safety and Environmental Protection, 117, 408-425. doi:10.1016/j.psep.2018.05.009Khuntia, J., Saldanha, T. J. V., Mithas, S., & Sambamurthy, V. (2018). Information Technology and Sustainability: Evidence from an Emerging Economy. Production and Operations Management, 27(4), 756-773. doi:10.1111/poms.12822Roy, S., Das, M., Ali, S. M., Raihan, A. S., Paul, S. K., & Kabir, G. (2020). Evaluating strategies for environmental sustainability in a supply chain of an emerging economy. Journal of Cleaner Production, 262, 121389. doi:10.1016/j.jclepro.2020.121389Morais, D. O. C., & Silvestre, B. S. (2018). Advancing social sustainability in supply chain management: Lessons from multiple case studies in an emerging economy. Journal of Cleaner Production, 199, 222-235. doi:10.1016/j.jclepro.2018.07.097Stindt, D. (2017). A generic planning approach for sustainable supply chain management - How to integrate concepts and methods to address the issues of sustainability? Journal of Cleaner Production, 153, 146-163. doi:10.1016/j.jclepro.2017.03.126MOSLEMIPOUR, G., LEE, T. S., & LOONG, Y. T. (2017). Performance Analysis of Intelligent Robust Facility Layout Design. Chinese Journal of Mechanical Engineering, 30(2), 407-418. doi:10.1007/s10033-017-0073-9Emami, S., & S. Nookabadi, A. (2013). Managing a new multi-objective model for the dynamic facility layout problem. The International Journal of Advanced Manufacturing Technology, 68(9-12), 2215-2228. doi:10.1007/s00170-013-4820-5Al Hawarneh, A., Bendak, S., & Ghanim, F. (2019). Dynamic facilities planning model for large scale construction projects. Automation in Construction, 98, 72-89. doi:10.1016/j.autcon.2018.11.021Pournaderi, N., Ghezavati, V. R., & Mozafari, M. (2019). Developing a mathematical model for the dynamic facility layout problem considering material handling system and optimizing it using cloud theory-based simulated annealing algorithm. SN Applied Sciences, 1(8). doi:10.1007/s42452-019-0865-xTuranoğlu, B., & Akkaya, G. (2018). A new hybrid heuristic algorithm based on bacterial foraging optimization for the dynamic facility layout problem. Expert Systems with Applications, 98, 93-104. doi:10.1016/j.eswa.2018.01.011Moslemipour, G., Lee, T. S., & Rilling, D. (2011). A review of intelligent approaches for designing dynamic and robust layouts in flexible manufacturing systems. The International Journal of Advanced Manufacturing Technology, 60(1-4), 11-27. doi:10.1007/s00170-011-3614-xTebaldi, L., Bigliardi, B., & Bottani, E. (2018). Sustainable Supply Chain and Innovation: A Review of the Recent Literature. Sustainability, 10(11), 3946. doi:10.3390/su10113946Tseng, M.-L., Islam, M. S., Karia, N., Fauzi, F. A., & Afrin, S. (2019). A literature review on green supply chain management: Trends and future challenges. Resources, Conservation and Recycling, 141, 145-162. doi:10.1016/j.resconrec.2018.10.009Ghobakhloo, M. (2020). Industry 4.0, digitization, and opportunities for sustainability. Journal of Cleaner Production, 252, 119869. doi:10.1016/j.jclepro.2019.119869Boar, A., Bastida, R., & Marimon, F. (2020). A Systematic Literature Review. Relationships between the Sharing Economy, Sustainability and Sustainable Development Goals. Sustainability, 12(17), 6744. doi:10.3390/su12176744Novais, L., Maqueira, J. M., & Ortiz-Bas, Á. (2019). A systematic literature review of cloud computing use in supply chain integration. Computers & Industrial Engineering, 129, 296-314. doi:10.1016/j.cie.2019.01.056Masi, D., Day, S., & Godsell, J. (2017). Supply Chain Configurations in the Circular Economy: A Systematic Literature Review. Sustainability, 9(9), 1602. doi:10.3390/su9091602Zavala-Alcívar, A., Verdecho, M.-J., & Alfaro-Saiz, J.-J. (2020). A Conceptual Framework to Manage Resilience and Increase Sustainability in the Supply Chain. Sustainability, 12(16), 6300. doi:10.3390/su12166300Li, K., Rollins, J., & Yan, E. (2017). Web of Science use in published research and review papers 1997–2017: a selective, dynamic, cross-domain, content-based analysis. Scientometrics, 115(1), 1-20. doi:10.1007/s11192-017-2622-5Kulturel-Konak, S., & Konak, A. (2014). A large-scale hybrid simulated annealing algorithm for cyclic facility layout problems. Engineering Optimization, 47(7), 963-978. doi:10.1080/0305215x.2014.933825Madhusudanan Pillai, V., Hunagund, I. B., & Krishnan, K. K. (2011). Design of robust layout for Dynamic Plant Layout Problems. Computers & Industrial Engineering, 61(3), 813-823. doi:10.1016/j.cie.2011.05.014Peng, Y., Zeng, T., Fan, L., Han, Y., & Xia, B. (2018). An Improved Genetic Algorithm Based Robust Approach for Stochastic Dynamic Facility Layout Problem. Discrete Dynamics in Nature and Society, 2018, 1-8. doi:10.1155/2018/1529058McKendall, A. R., & Hakobyan, A. (2010). Heuristics for the dynamic facility layout problem with unequal-area departments. European Journal of Operational Research, 201(1), 171-182. doi:10.1016/j.ejor.2009.02.028Yang, C.-L., Chuang, S.-P., & Hsu, T.-S. (2010). A genetic algorithm for dynamic facility planning in job shop manufacturing. The International Journal of Advanced Manufacturing Technology, 52(1-4), 303-309. doi:10.1007/s00170-010-2733-0Abedzadeh, M., Mazinani, M., Moradinasab, N., & Roghanian, E. (2012). Parallel variable neighborhood search for solving fuzzy multi-objective dynamic facility layout problem. The International Journal of Advanced Manufacturing Technology, 65(1-4), 197-211. doi:10.1007/s00170-012-4160-xGuan, X., Dai, X., Qiu, B., & Li, J. (2012). A revised electromagnetism-like mechanism for layout design of reconfigurable manufacturing system. Computers & Industrial Engineering, 63(1), 98-108. doi:10.1016/j.cie.2012.01.016Jolai, F., Tavakkoli-Moghaddam, R., & Taghipour, M. (2012). A multi-objective particle swarm optimisation algorithm for unequal sized dynamic facility layout problem with pickup/drop-off locations. International Journal of Production Research, 50(15), 4279-4293. doi:10.1080/00207543.2011.613863Kia, R., Baboli, A., Javadian, N., Tavakkoli-Moghaddam, R., Kazemi, M., & Khorrami, J. (2012). Solving a group layout design model of a dynamic cellular manufacturing system with alternative process routings, lot splitting and flexible reconfiguration by simulated annealing. Computers & Operations Research, 39(11), 2642-2658. doi:10.1016/j.cor.2012.01.012McKendall, A. R., & Liu, W.-H. (2012). New Tabu search heuristics for the dynamic facility layout problem. International Journal of Production Research, 50(3), 867-878. doi:10.1080/00207543.2010.545446Hosseini-Nasab, H., & Emami, L. (2013). A hybrid particle swarm optimisation for dynamic facility layout problem. International Journal of Production Research, 51(14), 4325-4335. doi:10.1080/00207543.2013.774486Kaveh, M., Dalfard, V. M., & Amiri, S. (2013). A new intelligent algorithm for dynamic facility layout problem in state of fuzzy constraints. Neural Computing and Applications, 24(5), 1179-1190. doi:10.1007/s00521-013-1339-5KIA, R., JAVADIAN, N., PAYDAR, M. M., & SAIDI-MEHRABAD, M. (2013). A SIMULATED ANNEALING FOR INTRA-CELL LAYOUT DESIGN OF DYNAMIC CELLULAR MANUFACTURING SYSTEMS WITH ROUTE SELECTION, PURCHASING MACHINES AND CELL RECONFIGURATION. Asia-Pacific Journal of Operational Research, 30(04), 1350004. doi:10.1142/s0217595913500048Mazinani, M., Abedzadeh, M., & Mohebali, N. (2012). Dynamic facility layout problem based on flexible bay structure and solving by genetic algorithm. The International Journal of Advanced Manufacturing Technology, 65(5-8), 929-943. doi:10.1007/s00170-012-4229-6Samarghandi, H., Taabayan, P., & Behroozi, M. (2013). Metaheuristics for fuzzy dynamic facility layout problem with unequal area constraints and closeness ratings. The International Journal of Advanced Manufacturing Technology, 67(9-12), 2701-2715. doi:10.1007/s00170-012-4685-zYu-Hsin Chen, G. (2013). A new data structure of solution representation in hybrid ant colony optimization for large dynamic facility layout problems. International Journal of Production Economics, 142(2), 362-371. doi:10.1016/j.ijpe.2012.12.012Bozorgi, N., Abedzadeh, M., & Zeinali, M. (2014). Tabu search heuristic for efficiency of dynamic facility layout problem. The International Journal of Advanced Manufacturing Technology, 77(1-4), 689-703. doi:10.1007/s00170-014-6460-9CHEN, G. Y.-H., & LO, J.-C. (2014). DYNAMIC FACILITY LAYOUT WITH MULTI-OBJECTIVES. Asia-Pacific Journal of Operational Research, 31(04), 1450027. doi:10.1142/s0217595914500274Hosseini, S., Khaled, A. A., & Vadlamani, S. (2014). Hybrid imperialist competitive algorithm, variable neighborhood search, and simulated annealing for dynamic facility layout problem. Neural Computing and Applications, 25(7-8), 1871-1885. doi:10.1007/s00521-014-1678-xKia, R., Khaksar-Haghani, F., Javadian, N., & Tavakkoli-Moghaddam, R. (2014). Solving a multi-floor layout design model of a dynamic cellular manufacturing system by an efficient genetic algorithm. Journal of Manufacturing Systems, 33(1), 218-232. doi:10.1016/j.jmsy.2013.12.005Nematian, J. (2014). A robust single row facility layout problem with fuzzy random variables. The International Journal of Advanced Manufacturing Technology, 72(1-4), 255-267. doi:10.1007/s00170-013-5564-yPourvaziri, H., & Naderi, B. (2014). A hybrid multi-population genetic algorithm for the dynamic facility layout problem. Applied Soft Computing, 24, 457-469. doi:10.1016/j.asoc.2014.06.051Derakhshan Asl, A., & Wong, K. Y. (2015). Solving unequal-area static and dynamic facility layout problems using modified particle swarm optimization. Journal of Intelligent Manufacturing, 28(6), 1317-1336. doi:10.1007/s10845-015-1053-5Li, L., Li, C., Ma, H., & Tang, Y. (2015). An Optimization Method for the Remanufacturing Dynamic Facility Layout Problem with Uncertainties. Discrete Dynamics in Nature and Society, 2015, 1-11. doi:10.1155/2015/685408Ulutas, B., & Islier, A. A. (2015). Dynamic facility layout problem in footwear industry. Journal of Manufacturing Systems, 36, 55-61. doi:10.1016/j.jmsy.2015.03.004Zarea Fazlelahi, F., Pournader, M., Gharakhani, M., & Sadjadi, S. J. (2016). A robust approach to design a single facility layout plan in dynamic manufacturing environments using a permutation-based genetic algorithm. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 230(12), 2264-2274. doi:10.1177/0954405415615728Hosseini, S. S., & Seifbarghy, M. (2016). A novel meta-heuristic algorithm for multi-objective dynamic facility layout problem. RAIRO - Operations Research, 50(4-5), 869-890. doi:10.1051/ro/2016057Pourvaziri, H., & Pierreval, H. (2017). Dynamic facility layout problem based on open queuing network theory. European Journal of Operational Research, 259(2), 538-553. doi:10.1016/j.ejor.2016.11.011Tayal, A., & Singh, S. P. (2016). Integrating big data analytic and hybrid firefly-chaotic simulated annealing approach for facility layout problem. Annals of Operations Research, 270(1-2), 489-514. doi:10.1007/s10479-016-2237-xKumar, R., & Singh, S. P. (2017). A similarity score-based two-phase heuristic approach to solve the dynamic cellular facility layout for manufacturing systems. Engineering Optimization, 49(11), 1848-1867. doi:10.1080/0305215x.2016.1274205Liu, J., Wang, D., He, K., & Xue, Y. (2017). Combining Wang–Landau sampling algorithm and heuristics for solving the unequal-area dynamic facility layout problem. 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Facility layout planning. An extended literature review

[EN] Facility layout planning (FLP) involves a set of design problems related to the arrangement of the elements that shape industrial production systems in a physical space. The fact that they are considered one of the most important design decisions as part of business operation strategies, and their proven repercussion on production systems' operation costs, efficiency and productivity, mean that this theme has been widely addressed in science. In this context, the present article offers a scientific literature review about FLP from the operations management perspective. The 232 reviewed articles were classified as a large taxonomy based on type of problem, approach and planning stage and characteristics of production facilities by configuring the material handling system and methods to generate and assess layout alternatives. We stress that the generation of layout alternatives was done mainly using mathematical optimisation models, specifically discrete quadratic programming models for similar sized departments, or continuous linear and non-linear mixed integer programming models for different sized departments. Other approaches followed to generate layout alternatives were expert's knowledge and specialised software packages. Generally speaking, the most frequent solution algorithms were metaheuristics.The research leading to these results received funding from the European Union H2020 Program under grant agreement No 958205 `Industrial Data Services for Quality Control in Smart Manufacturing (i4Q)'and from the Spanish Ministry of Science, Innovation and Universities under grant agreement RTI2018-101344-B-I00 `Optimisation of zerodefectsproduction technologies enabling supply chains 4.0 (CADS4.0)'Pérez-Gosende, P.; Mula, J.; Díaz-Madroñero Boluda, FM. (2021). Facility layout planning. An extended literature review. International Journal of Production Research. 59(12):3777-3816. https://doi.org/10.1080/00207543.2021.189717637773816591

Master production schedule using robust optimization approaches in an automobile second-tier supplier

[EN] This paper considers a real-world automobile second-tier supplier that manufactures decorative surface finishings of injected parts provided by several suppliers, and which devises its master production schedule by a manual spreadsheet-based procedure. The imprecise production time in this manufacturer's production process is incorporated into a deterministic mathematical programming model to address this problem by two robust optimization approaches. The proposed model and the corresponding robust solution methodology improve production plans by optimizing the production, inventory and backlogging costs, and demonstrate the their feasibility for a realistic master production schedule problem that outperforms the heuristic decision-making procedure currently being applied in the firm under study.Funding was provided by Horizon 2020 Framework Programme (Grant Agreement No. 636909) in the frame of the "Cloud Collaborative Manufacturing Networks" (C2NET) project.Martín, AG.; Díaz-Madroñero Boluda, FM.; Mula, J. (2020). Master production schedule using robust optimization approaches in an automobile second-tier supplier. Central European Journal of Operations Research. 28(1):143-166. https://doi.org/10.1007/s10100-019-00607-2S143166281Alem DJ, Morabito R (2012) Production planning in furniture settings via robust optimization. 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A review of discrete-time optimization models for tactical production planning

This is an Accepted Manuscript of an article published in International Journal of Production Research on 27 Mar 2014, available online: http://doi.org/10.1080/00207543.2014.899721[EN] This study presents a review of optimization models for tactical production planning. The objective of this research is to identify streams and future research directions in this field based on the different classification criteria proposed. The major findings indicate that: (1) the most popular production-planning area is master production scheduling with a big-bucket time-type period; (2) most of the considered limited resources correspond to productive resources and, to a lesser extent, to inventory capacities; (3) the consideration of backlogs, set-up times, parallel machines, overtime capacities and network-type multisite configuration stand out in terms of extensions; (4) the most widely used modelling approach is linear/integer/mixed integer linear programming solved with exact algorithms, such as branch-and-bound, in commercial MIP solvers; (5) CPLEX, C and its variants and Lindo/Lingo are the most popular development tools among solvers, programming languages and modelling languages, respectively; (6) most works perform numerical experiments with random created instances, while a small number of works were validated by real-world data from industrial firms, of which the most popular are sawmills, wood and furniture, automobile and semiconductors and electronic devices.This study has been funded by the Universitat Politècnica de València projects: ‘Material Requirement Planning Fourth Generation (MRPIV)’ (Ref. PAID-05-12) and ‘Quantitative Models for the Design of Socially Responsible Supply Chains under Uncertainty Conditions. Application of Solution Strategies based on Hybrid Metaheuristics’ (PAID-06-12).Díaz-Madroñero Boluda, FM.; Mula, J.; Peidro Payá, D. (2014). A review of discrete-time optimization models for tactical production planning. International Journal of Production Research. 52(17):5171-5205. doi:10.1080/00207543.2014.899721S51715205521

Optimising the Analysis Stage in the Internationalisation of Manufacturing Operations

[EN] The internationalisation of the manufacturing operations process includes decision-making about new facility implementation (NFI) and global supplier network development (GSND), whose first step is to analyse the situation of a company and its environment. The purpose of this paper is to investigate the optimal design of a manufacturing production and distribution network for global small-and medium-sized enterprises (SMEs). This research uses a mixed-integer linear programming (MILP) model to support decision-making in the analysis stage of the internationalisation of manufacturing operations for global SMEs. A real-world case study is presented to illustrate the application of the proposed model. Different scenarios were evaluated not only to identify the strengths and limitations of the mathematical programming model, but to also provide support for the next strategic decisions that the examined company has to make in the near future.This work was supported by the Spanish Ministry of Science, Innovation and Universities project entitled `Optimisation of zero-defects production technologies enabling supply chains 4.0 (CADS4.0)' (RTI2018-101344-B-I00).Comer, F.; Mula, J.; Díaz-Madroñero Boluda, FM.; Grillo, H. (2021). Optimising the Analysis Stage in the Internationalisation of Manufacturing Operations. The South African Journal of Industrial Engineering. 32(2):124-132. https://doi.org/10.7166/32-2-2371S12413232