Monte Carlo Enhancement via Simulation Decomposition: A “Must-Have” Inclusion for Many Disciplines

Published Online:https://doi.org/10.1287/ited.2019.0240

References

  • Arnold U, Yildiz Ö (2015) Economic risk analysis of decentralized renewable energy infrastructures—A Monte Carlo simulation approach. Renewable Energy 77:227–239.CrossrefGoogle Scholar
  • Christie DS (2018) Build your own Monte Carlo spreadsheet. Spreadsheets Ed. 11(1):1–16.Google Scholar
  • Deviatkin I, Khan M, Ernst E, Horttanainen M (2019) Wooden and plastic pallets: A review of life cycle assessment (LCA) studies. Sustainability 11(20):5750.CrossrefGoogle Scholar
  • Fulton L, McMurry LP, Kerr CB (2009) A Monte Carlo simulation of air ambulance requirements during major combat operations. Military Medicine 174(6):610–614.CrossrefGoogle Scholar
  • García-Redondo F, López-Vallejo M, Ituero P, Barrio CL (2012) A CAD framework for the characterization and use of memristor models. 2012 Internat. Conf. Synthesis Model. Anal. Simulation Methods Appl. Circuit Design (SMACD) (IEEE, Piscataway, NJ), 25–28.Google Scholar
  • Kozlova M, Yeomans JS (2019) Multi-variable simulation decomposition in environmental planning: An application to carbon capture and storage. J. Environ. Informatics Lett. 1(1):20–26.CrossrefGoogle Scholar
  • Kozlova M, Collan M, Luukka P (2016) Simulation decomposition: New approach for better simulation analysis of multi-variable investment projects. Fuzzy Econom. Rev. 21(2):3–18.Google Scholar
  • Kozlova M, Collan M, Luukka P (2018a) Simple example for decomposition. Working paper, LUT University, Lappeenranta, Finland.Google Scholar
  • Kozlova M, Collan M, Luukka P (2018b) Matlab function for simulation decomposition. Working paper, LUT University, Lappeenranta, Finland.Google Scholar
  • New M, Hulme M (2000) Representing uncertainty in climate change scenarios: A Monte-Carlo approach. Integrated Assessment 1(3):203–213.CrossrefGoogle Scholar
  • Shonkwiler RW, Mendivil F (2009) Explorations in Monte Carlo Methods, Undergraduate Texts in Mathematics (Springer Science & Business Media, Berlin).CrossrefGoogle Scholar
  • Srinivasan R, Cook J, Lubeck O (2006) Ultra-fast CPU performance prediction: Extending the Monte Carlo approach. 2006 18th Internat. Sympos. Comput. Architecture High Performance Comput. (SBAC-PAD'06) (IEEE, Piscataway, NJ), 107–116.Google Scholar
  • Thinkstep AG (2019) GaBi software system and database for life cycle engineering. Accessed February 1, 2020, http://www.gabi-software.com/finland/databases/gabi-database-edition-2019/Google Scholar
  • Van der Straaten T, Kathawala G, Trellakis A, Eisenberg RS, Ravaioli U (2005) BioMOCA—A Boltzmann transport Monte Carlo model for ion channel simulation. Molecular Simulation 31(2-3):151–171.CrossrefGoogle Scholar
  • Warren WG, Shelton PA, Stenson GB (1997) Quantifying some of the major sources of uncertainty associated with estimates of harp seal prey consumption. Part 1: Uncertainty in the estimates of harp seal population size. J. Northwest Atlantic Fishery Sci. 22:289–302.CrossrefGoogle Scholar
  • Zio E, ed. (2013) The Monte Carlo Simulation Method for System Reliability and Risk Analysis (Springer, London).CrossrefGoogle Scholar
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