Identyfikatory
Warianty tytułu
Model optymalizacji czasu wymiany floty. Analiza porównawcza flot miejskiego transportu publicznego z zastosowaniem symulacji Monte Carlo
Języki publikacji
Abstrakty
This paper presents a comparative analysis of operation and maintenance costs of the transport fleets in two countries: Spain and Brazil. For this analysis, the research proposed an optimization model which is a combination of the traditional Life Cycle Cost Analysis methodology (LCC) and simulation model Monte Carlo. The results indicated the successful of model and show the lower cost in the Brazilian fleet. The evidences may be useful for other practices and researches.
W niniejszej pracy przedstawiono analizę kosztów pracy i utrzymania flot transportowych w dwóch krajach: Hiszpanii i Brazylii. Dla celów analizy, zaproponowano model optymalizacji stanowiący połączenie tradycyjnej Analizy Kosztów Cyklu Życia (LCC) oraz modelu symulacji Monte Carlo. wyniki potwierdziły trafność modelu oraz pokazały, że koszty ponoszone w przypadku floty brazylijskiej były niższe. Zaproponowany model może znaleźć zastosowanie zarówno w praktyce jak i w dalszych badaniach.
Czasopismo
Rocznik
Tom
Strony
151--157
Opis fizyczny
Bibliogr. 19 poz., rys., tab.
Twórcy
autor
- Universitat Politècnica de València camino de Vera, s/n, 46022, Valencia - Spain
autor
- Universitat Politècnica de València camino de Vera, s/n, 46022, Valencia - Spain
autor
- Department of Mechanical engineering Federal Technological University of Paraná av 7 de setembro, 3165, 80230-901- c uritiba - Paraná - Brazil
Bibliografia
- 1. Avila C R, Beck A T. New method for efficient Monte Carlo–Neumann solution of linear stochastic systems. Probabilistic Engineering Mechanics 2015; 40: 90–96, http://dx.doi.org/10.1016/j.probengmech.2015.02.006.
- 2. Banar M, Özdemir A. An evaluation of railway passenger transport in Turkey using life cycle assessment and life cycle cost methods. Transportation Research Part D 2015; 41: 88-105, http://dx.doi.org/10.1016/j.trd.2015.09.017.
- 3. Boudart J, Figliozzi M. Key Variables Affecting Decisions of Bus Replacement Age and Total Costs. Transportation Research Board 2012. 2274: 109-113, http://dx.doi.org/10.3141/2274-12.
- 4. Clark N N, Zhen F, Wayne S W. Assessment of Hybrid-Electric Transit Bus Technology. Washington D.C. Transportation Research Board 2009.
- 5. Collan M, LIU S. Fuzzy Logic and Intelligent Agents: Towards the next step of capital budgeting decision support. Industrial Management Data Systems 2003: 103: 410-424, https://doi.org/10.1108/02635570310479981.
- 6. Di J, Hauke L. Optimal Fleet Utilization and Replacement. Transportation Research Part E 2000: 36(1): 3-20, https://doi.org/10.1016/S1366-5545(99)00021-6.
- 7. Dhillon B S. Life Cycle Costing For Engineers. London: CRC Press 2010.
- 8. Emblemsvag J. Life-Cycle Costing, Using Activity-based Carlo, Monte To, Methods Costs, Manage Future. Hoboken New Jersey-USA: John Wiley & Sons, Inc. 2003.
- 9. Fan W, Randy M, Gemar M, Brown L. A Stochastic Dynamic Programming Approach for the Equipment Replacement Optimization with Probabilistic Vehicle Utilization. The 91st Annual Meeting of Transportation Research Board. Washington D.C. 2012.
- 10. Feng W, Figliozzi M. An economic and technological analysis of the key factors affecting the competitiveness of electric commercial vehicles: A case study from the USA market. Transportation Research Part C: Emerging Technologies 2012; 26: 135-145, https://doi.org/10.1016/j.trc.2012.06.007.
- 11. Gransberg D, O'Connor E. Major Equipment Life-cycle Cost Analysis. Institute for Transportation Iowa State University. Minnesota Department of Transportation Research Services & Library, USA 2015.
- 12. Khasnabis S, Alsaidi E, Ellis R D. Optimal allocation of resources to meet transit fleet requirements. Journal of Transportation Engineering 2002; 128(6): 509 -518, https://doi.org/10.1061/(ASCE)0733-947X(2002)128:6(509).
- 13. Kim D S., Porter D J, Kriett P, Mbugua W, Wagner T. Fleet Replacement Modeling. Final Report, Oregon State University, School of Mechanical, Industrial and Manufacturing Engineering 2009.
- 14. Laver R, Schneck D, Skorupski D, Brady S, Cham L, Hamilton B A. Useful Life of Transit Buses and Vans. Washington D.C: Federal Transit Administration 2007.
- 15. Nowakowski T, Młyńczak M, Werbińska-Wojciechowska S, Dziaduch I, Tubis A. Life Cycle Costs of passenger transportation system. Case study of Wroclaw city agglomeration 5. JPSRA 2014; 5: 109-120.
- 16. Pinar Keles, Hartman J C. Case Study: Bus Fleet Replacement. The Engineering Economist 2004; 49(3): 253-278, https://doi.org/10.1080/00137910490498951.
- 17. Rymarz J, Niewczas A, Krzyżak A. Comparison of operational availability of public city buses by analysis of variance. Eksploatacja i Niezawodnosc–Maintenance and Reliability 2016; 18 (3):373–378, http://dx. doi.org/10.17531/ein.2016.3.8.
- 18. Singh D, Tiong R L K. Development of life cycle costing framework for highway bridges In Myanmar. International Journal of Project Management 2005; 23: 37–44, http://dx.doi:10.1016/j.ijproman.2004.05.010.
- 19. Tchórzewska-Cieślak B, Pietrucha-Urbanik K, Urbanik M. Analysis of the gas network failure and failure prediction using the Monte Carlo simulation method. Eksploatacja i Niezawodność – Maintenance and Reliability 2016; 18 (2): 254–259, http://dx.doi.org/10.17531/ ein.2016.2.13
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-e368ccee-92dc-4bdc-a522-191eab6065fb