Modelling and simulation in business, economics and management
Abstract
Modelling and Simulation in Business, Economics and Management. Technological and Economic Development of Economy, 25(4), pp. 571-575.
Keyword : editorial
How to Cite
León-Castro, E., Merigó, J. M., Avilés-Ochoa, E., Gil-Lafuente, A. M., & Herrera-Viedma, E. (2019). Modelling and simulation in business, economics and management. Technological and Economic Development of Economy, 25(4), 571-575. https://doi.org/10.3846/tede.2019.9365
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Azab, A., & AlGeddawy, T. (2012). Simulation methods for changeable manufacturing. Procedia CIRP, 3, 179-184. https://doi.org/10.1016/j.procir.2012.07.032
Banomyong, R., & Sopadang, A. (2010). Using Monte Carlo simulation to refine emergency logistics response models: a case study. International Journal of Physical Distribution & Logistics Management, 40(8/9), 709-721. https://doi.org/10.1108/09600031011079346
Blanco-Mesa, F., León-Castro, E., & Merigó, J. M. (2018). Bonferroni induced heavy operators in ERM decision-making: A case on large companies in Colombia. Applied Soft Computing, 72, 371-391. https://doi.org/10.1016/j.asoc.2018.08.001
Blanco-Mesa, F., Merigó, J. M., & Gil-Lafuente, A. M. (2017). Fuzzy decision making: a bibliometric-based review. Journal of Intelligent & Fuzzy Systems, 32(3), 2033-2050. https://doi.org/10.3233/JIFS-161640
Cabrerizo, F. J., Al-Hmouz, R., Morfeq, A., Balamash, A. S., Martínez, M. A., & Herrera-Viedma, E. (2017). Soft consensus measures in group decision making using unbalanced fuzzy linguistic information. Soft Computing, 21(11), 3037-3050. https://doi.org/10.1007/s00500-015-1989-6
Cabrerizo, F. J., Herrera-Viedma, E., & Pedrycz, W. (2013). A method based on PSO and granular computing of linguistic information to solve group decision making problems defined in heterogeneous contexts. European Journal of Operational Research, 230(3), 624-633. https://doi.org/10.1016/j.ejor.2013.04.046
Campuzano, F., Mula, J., & Peidro, D. (2010). Fuzzy estimations and system dynamics for improving supply chains. Fuzzy Sets and Systems, 161(11), 1530-1542. https://doi.org/10.1016/j.fss.2009.12.002
Capuano, N., Chiclana, F., Fujita, H., Herrera-Viedma, E., & Loia, V. (2018). Fuzzy group decision making with incomplete information guided by social influence. IEEE Transactions on Fuzzy Systems, 26(3), 1704-1718. https://doi.org/10.1109/TFUZZ.2017.2744605
Carrasco, R. A., Blasco, M. F., García-Madariaga, J., Pedreño-Santos, A., & Herrera-Viedma, E. (2018). A model to obtain a SERVPERF scale evaluation of the CRM customer complaints: An application to the 4G telecommunications sector. Technological and Economic Development of Economy, 24(4), 1606-1629. https://doi.org/10.3846/tede.2018.5080
Cid-López, A., Hornos, M. J., Carrasco-González, R. A., & Herrera-Viedma, E. (2018). Prioritization of the launch of ICT products and services through linguistic multi-criteria decision-making. Technological and Economic Development of Economy, 24(3), 1231-1257. https://doi.org/10.3846/tede.2018.1423
Cheng, C. H., Wei, L. Y., Liu, J. W., & Chen, T. L. (2013). OWA-based ANFIS model for TAIEX forecasting. Economic Modelling, 30, 442-448. https://doi.org/10.1016/j.econmod.2012.09.047
Datta, S., Samantra, C., Mahapatra, S. S., Banerjee, S., & Bandyopadhyay, A. (2012). Green supplier evaluation and selection using VIKOR method embedded in fuzzy expert system with interval-valued fuzzy numbers. International Journal of Procurement Management, 5(5), 647-678. https://doi.org/10.1504/IJPM.2012.048880
Dyson, B., & Chang, N. B. (2005). Forecasting municipal solid waste generation in a fast-growing urban region with system dynamics modeling. Waste Management, 25(7), 669-679. https://doi.org/10.1016/j.wasman.2004.10.005
Engemann, K. J., Filev, D. P., & Yager, R. R. (1996). Modelling decision making using immediate probabilities. International Journal of General Systems, 24(3), 281-294. https://doi.org/10.1080/03081079608945123
Gil-Aluja, J. (1999). Elements for a theory of decision in uncertainty (Vol. 32). Springer Science & Business Media. https://doi.org/10.1007/978-1-4757-3011-1
Jahangirian, M., Eldabi, T., Naseer, A., Stergioulas, L. K., & Young, T. (2010). Simulation in manufacturing and business: A review. European Journal of Operational Research, 203(1), 1-13. https://doi.org/10.1016/j.ejor.2009.06.004
Kacprzyk, J., Yager, R. R., & Merigó, J. M. (2019). Towards human centric aggregation via the ordered weighted aggregation operators and linguistic data summaries: A new perspective on Zadeh’s inspirations. IEEE Computational Intelligence Magazine, 14(1), 16-30. https://doi.org/10.1109/MCI.2018.2881641
León-Castro, E., Avilés-Ochoa, E., Merigó, J. M., & Gil-Lafuente, A. M. (2018). Heavy moving averages and their application in econometric forecasting. Cybernetics and Systems, 49(1), 26-43. https://doi.org/10.1080/01969722.2017.1412883
Merigó, J. M. (2010). Fuzzy decision making with immediate probabilities. Computers & Industrial Engineering, 58(4), 651-657. https://doi.org/10.1016/j.cie.2010.01.007
Merigó, J. M., Palacios-Marqués, D., & Soto-Acosta, P. (2017). Distance measures, weighted averages, OWA operators and Bonferroni means. Applied Soft Computing, 50, 356-366. https://doi.org/10.1016/j.asoc.2016.11.024
Mourtzis, D., Doukas, M., & Bernidaki, D. (2014). Simulation in manufacturing: Review and challenges. Procedia CIRP, 25, 213-229. https://doi.org/10.1016/j.procir.2014.10.032
Olson, D. L., & Wu, D. D. (2010). Enterprise risk management models. New York: Springer. https://doi.org/10.1007/978-3-642-11474-8
Perez, I. J., Cabrerizo, F. J., Alonso, S., Dong, Y. C., Chiclana, F., & Herrera-Viedma, E. (2018). On dynamic consensus processes in group decision making problems. Information Sciences, 459, 20-35. https://doi.org/10.1016/j.ins.2018.05.017
Qi, C., & Chang, N. B. (2011). System dynamics modeling for municipal water demand estimation in an urban region under uncertain economic impacts. Journal of Environmental Management, 92(6), 1628-1641. https://doi.org/10.1016/j.jenvman.2011.01.020
Sandhu, M. A., Helo, P., & Kristianto, Y. (2013). Steel supply chain management by simulation modelling. Benchmarking: an International Journal, 20(1), 45-61. https://doi.org/10.1108/14635771311299489
Sari, K., Oktay, F., & Tevfik, A. T. (2010). A simulation model for managing outsourcing decisions. International Journal of Management and Enterprise Development, 9(2), 132-146. https://doi.org/10.1504/IJMED.2010.036118
Ustundag, A., Kılınç, M. S., & Cevikcan, E. (2010). Fuzzy rule-based system for the economic analysis of RFID investments. Expert Systems with Applications, 37(7), 5300-5306. https://doi.org/10.1016/j.eswa.2010.01.009
Zadeh, L. (1965). Fuzzy sets. Information and Control, 8(3), 338-353. https://doi.org/10.1016/S0019-9958(65)90241-X
Banomyong, R., & Sopadang, A. (2010). Using Monte Carlo simulation to refine emergency logistics response models: a case study. International Journal of Physical Distribution & Logistics Management, 40(8/9), 709-721. https://doi.org/10.1108/09600031011079346
Blanco-Mesa, F., León-Castro, E., & Merigó, J. M. (2018). Bonferroni induced heavy operators in ERM decision-making: A case on large companies in Colombia. Applied Soft Computing, 72, 371-391. https://doi.org/10.1016/j.asoc.2018.08.001
Blanco-Mesa, F., Merigó, J. M., & Gil-Lafuente, A. M. (2017). Fuzzy decision making: a bibliometric-based review. Journal of Intelligent & Fuzzy Systems, 32(3), 2033-2050. https://doi.org/10.3233/JIFS-161640
Cabrerizo, F. J., Al-Hmouz, R., Morfeq, A., Balamash, A. S., Martínez, M. A., & Herrera-Viedma, E. (2017). Soft consensus measures in group decision making using unbalanced fuzzy linguistic information. Soft Computing, 21(11), 3037-3050. https://doi.org/10.1007/s00500-015-1989-6
Cabrerizo, F. J., Herrera-Viedma, E., & Pedrycz, W. (2013). A method based on PSO and granular computing of linguistic information to solve group decision making problems defined in heterogeneous contexts. European Journal of Operational Research, 230(3), 624-633. https://doi.org/10.1016/j.ejor.2013.04.046
Campuzano, F., Mula, J., & Peidro, D. (2010). Fuzzy estimations and system dynamics for improving supply chains. Fuzzy Sets and Systems, 161(11), 1530-1542. https://doi.org/10.1016/j.fss.2009.12.002
Capuano, N., Chiclana, F., Fujita, H., Herrera-Viedma, E., & Loia, V. (2018). Fuzzy group decision making with incomplete information guided by social influence. IEEE Transactions on Fuzzy Systems, 26(3), 1704-1718. https://doi.org/10.1109/TFUZZ.2017.2744605
Carrasco, R. A., Blasco, M. F., García-Madariaga, J., Pedreño-Santos, A., & Herrera-Viedma, E. (2018). A model to obtain a SERVPERF scale evaluation of the CRM customer complaints: An application to the 4G telecommunications sector. Technological and Economic Development of Economy, 24(4), 1606-1629. https://doi.org/10.3846/tede.2018.5080
Cid-López, A., Hornos, M. J., Carrasco-González, R. A., & Herrera-Viedma, E. (2018). Prioritization of the launch of ICT products and services through linguistic multi-criteria decision-making. Technological and Economic Development of Economy, 24(3), 1231-1257. https://doi.org/10.3846/tede.2018.1423
Cheng, C. H., Wei, L. Y., Liu, J. W., & Chen, T. L. (2013). OWA-based ANFIS model for TAIEX forecasting. Economic Modelling, 30, 442-448. https://doi.org/10.1016/j.econmod.2012.09.047
Datta, S., Samantra, C., Mahapatra, S. S., Banerjee, S., & Bandyopadhyay, A. (2012). Green supplier evaluation and selection using VIKOR method embedded in fuzzy expert system with interval-valued fuzzy numbers. International Journal of Procurement Management, 5(5), 647-678. https://doi.org/10.1504/IJPM.2012.048880
Dyson, B., & Chang, N. B. (2005). Forecasting municipal solid waste generation in a fast-growing urban region with system dynamics modeling. Waste Management, 25(7), 669-679. https://doi.org/10.1016/j.wasman.2004.10.005
Engemann, K. J., Filev, D. P., & Yager, R. R. (1996). Modelling decision making using immediate probabilities. International Journal of General Systems, 24(3), 281-294. https://doi.org/10.1080/03081079608945123
Gil-Aluja, J. (1999). Elements for a theory of decision in uncertainty (Vol. 32). Springer Science & Business Media. https://doi.org/10.1007/978-1-4757-3011-1
Jahangirian, M., Eldabi, T., Naseer, A., Stergioulas, L. K., & Young, T. (2010). Simulation in manufacturing and business: A review. European Journal of Operational Research, 203(1), 1-13. https://doi.org/10.1016/j.ejor.2009.06.004
Kacprzyk, J., Yager, R. R., & Merigó, J. M. (2019). Towards human centric aggregation via the ordered weighted aggregation operators and linguistic data summaries: A new perspective on Zadeh’s inspirations. IEEE Computational Intelligence Magazine, 14(1), 16-30. https://doi.org/10.1109/MCI.2018.2881641
León-Castro, E., Avilés-Ochoa, E., Merigó, J. M., & Gil-Lafuente, A. M. (2018). Heavy moving averages and their application in econometric forecasting. Cybernetics and Systems, 49(1), 26-43. https://doi.org/10.1080/01969722.2017.1412883
Merigó, J. M. (2010). Fuzzy decision making with immediate probabilities. Computers & Industrial Engineering, 58(4), 651-657. https://doi.org/10.1016/j.cie.2010.01.007
Merigó, J. M., Palacios-Marqués, D., & Soto-Acosta, P. (2017). Distance measures, weighted averages, OWA operators and Bonferroni means. Applied Soft Computing, 50, 356-366. https://doi.org/10.1016/j.asoc.2016.11.024
Mourtzis, D., Doukas, M., & Bernidaki, D. (2014). Simulation in manufacturing: Review and challenges. Procedia CIRP, 25, 213-229. https://doi.org/10.1016/j.procir.2014.10.032
Olson, D. L., & Wu, D. D. (2010). Enterprise risk management models. New York: Springer. https://doi.org/10.1007/978-3-642-11474-8
Perez, I. J., Cabrerizo, F. J., Alonso, S., Dong, Y. C., Chiclana, F., & Herrera-Viedma, E. (2018). On dynamic consensus processes in group decision making problems. Information Sciences, 459, 20-35. https://doi.org/10.1016/j.ins.2018.05.017
Qi, C., & Chang, N. B. (2011). System dynamics modeling for municipal water demand estimation in an urban region under uncertain economic impacts. Journal of Environmental Management, 92(6), 1628-1641. https://doi.org/10.1016/j.jenvman.2011.01.020
Sandhu, M. A., Helo, P., & Kristianto, Y. (2013). Steel supply chain management by simulation modelling. Benchmarking: an International Journal, 20(1), 45-61. https://doi.org/10.1108/14635771311299489
Sari, K., Oktay, F., & Tevfik, A. T. (2010). A simulation model for managing outsourcing decisions. International Journal of Management and Enterprise Development, 9(2), 132-146. https://doi.org/10.1504/IJMED.2010.036118
Ustundag, A., Kılınç, M. S., & Cevikcan, E. (2010). Fuzzy rule-based system for the economic analysis of RFID investments. Expert Systems with Applications, 37(7), 5300-5306. https://doi.org/10.1016/j.eswa.2010.01.009
Zadeh, L. (1965). Fuzzy sets. Information and Control, 8(3), 338-353. https://doi.org/10.1016/S0019-9958(65)90241-X