Skip to main content
SpringerLink
Log in

Harmony Search Algorithm for Transport Energy Demand Modeling

  • Chapter
Music-Inspired Harmony Search Algorithm

Part of the book series: Studies in Computational Intelligence ((SCI,volume 191))

Abstract

The transport sector is one of the major consumers of energy production throughout the world. Thus, the estimation of medium and long-term energy consumption based on socio-economic and transport related indicators is a critical issue on a global scale. This chapter reviews the harmony search (HS) applications to transport energy modeling problems. The models reviewed in this chapter are in the form of linear, exponential and quadratic mathematical expressions, and they are applied to transportation sector energy consumption. Convergence behavior of the HS during the modeling is tested. Performance of each HS model is compared according to an absolute error between observed data and predicted data. Results showed the HS method can be applied to the transport energy modeling issues.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Nathwani, J.S., Siddall, E., Lind, N.C.: Energy for 300 years. Institute for Risk Research, University of Waterloo, Waterloo (1992)

    Google Scholar 

  2. Dincer, I., Dost, S.: Energy and GDP. Int. J. Energy Res. 21, 153–167 (1997)

    Article  Google Scholar 

  3. Faiz, A.: Automotive emissions in developing countries-relative implications for global warming, acidification and urban air quality. Transportation Research (Part A) 27, 167–186 (1993)

    Google Scholar 

  4. Colvile, R.N., Hutchinson, E.J., Mindell, J.S., Warren, R.F.: The transport sector as a source of air pollution. Atmospheric Environment 35, 1537–1565 (2001)

    Article  Google Scholar 

  5. World Business Council for Sustainable Development, World mobility at the end of the twentieth century and its sustainability. WBCSD, Geneva (2001)

    Google Scholar 

  6. Anderson, W.P., Kanaroglou, P.S., Miller, E.J.: Urban form, energy and the environment: A review of issues, evidence and policy. Urban Studies 33, 7–35 (1996)

    Article  Google Scholar 

  7. Potoglou, D., Kanaroglou, P.S.: Carbon monoxide emissions from passenger vehicles: predictive mapping with an application to Hamilton, Canada. Transportation Research (Part D) 10, 97–109 (2005)

    Article  Google Scholar 

  8. Ceylan, H., Ceylan, H., Haldenbilen, S., Baskan, O.: Transport energy modeling with meta-heuristic harmony search algorithm, an application to Turkey. Energy Policy 36, 2527–2535 (2008)

    Article  Google Scholar 

  9. Asmann, D., Sieber, N.: Transport in developing countries: renewable energy versus energy reduction. Transport Reviews 25, 719–738 (2005)

    Article  Google Scholar 

  10. International Energy Agency (IEA), World energy outlook 2005: middle east and north africa insights. OECD/IEA Publishers, Paris (2005)

    Google Scholar 

  11. Haldenbilen, S., Ceylan, H.: Genetic algorithm approach to estimate transport energy demand in Turkey. Energy Policy 33, 89–98 (2005)

    Article  Google Scholar 

  12. World Energy Council-Turkish National Committee, Energy Statistics. WEC-TNC, Ankara (2006) (in Turkish)

    Google Scholar 

  13. Ceylan, H., Ozturk, H.K.: Estimating energy demand of Turkey based on economic indicators using genetic algorithm approach. Energy Conversion and Management 45, 2525–2537 (2004)

    Article  Google Scholar 

  14. Canyurt, O.E., Ozturk, H.K.: Three different applications of genetic algorithm search techniques on oil demand estimation. Energy Conversation and Management 47, 2148–3138 (2006)

    Google Scholar 

  15. Canyurt, O.E., Ozturk, H.K., Hepbasli, A., Utlu, Z.: Genetic algorithm approaches for the transport energy demand estimation: model development and application. Energy Sources (Part A) 28, 1405–1413 (2006)

    Google Scholar 

  16. Ozcelik, Y., Hepbasli, A.: Estimating petroleum energy production and consumption using a simulated annealing approach. Energy Sources (Part B: Economics, Planning and Policy) 1, 255–265 (2006)

    Article  Google Scholar 

  17. Gilland, B.: Energy for the 21st century: an engineer’s view. Endeavour 14, 80–86 (1990)

    Article  Google Scholar 

  18. Lakshminarayana, G.S.: Importance of long range energy demand forecasting in power system planning. Journal of Irrigation and Power 48, 29–38 (1991)

    Google Scholar 

  19. Unler, A.: Improvement of energy demand forecasts using swarm intelligence: The case of Turkey with projections to 2025. Energy Policy 36, 1937–1944 (2008)

    Article  Google Scholar 

  20. Toksari, M.D.: Ant colony optimization approach to estimate energy demand in Turkey. Energy Policy 35, 3984–3990 (2007)

    Article  Google Scholar 

  21. Rijal, K., Bansal, N.K., Grover, P.D.: Rural household energy demand modeling. Energy Economics 10, 279–288 (1990)

    Article  Google Scholar 

  22. Iniyan, S., Sumathy, K., Suganthy, L., Samuel, A.A.: Sensitivity analysis of optimal renewable energy mathematical model on demand variations. Energy Conversation & Management 41, 199–211 (2000)

    Article  Google Scholar 

  23. Demirbas, A.: Energy balance, energy sources, energy policy, future developments and energy investments in Turkey. Energy Conversion and Management 42, 1239–1258 (2001)

    Article  Google Scholar 

  24. Yumurtaci, Z., Asmaz, E.: Electric energy demand of Turkey for the year 2050. Energy Sources 26, 1157–1164 (2004)

    Article  Google Scholar 

  25. Sozen, A., Arcaklioglu, E., Ozkaymak, M.: Modeling of the Turkey’s net energy consumption using artificial neural network. International Journal of Computer Applications in Technology 22, 130–136 (2005)

    Article  Google Scholar 

  26. Akay, D., Atak, M.: Grey prediction with rolling mechanism for electricity demand forecasting of Turkey. Energy 32, 1670–1675 (2007)

    Article  Google Scholar 

  27. Sozen, A., Arcaklioglu, E.: Prospects for future projections of the basic energy sources in Turkey. Energy Sources (Part B: Economics, Planning, and Policy) 2, 183–201 (2007)

    Article  Google Scholar 

  28. Gilland, B.: Population, economic growth, and energy demand, 1985–2020. Population and Development Review 14, 233–244 (1988)

    Article  Google Scholar 

  29. Gungor, Z., Arikan, F.: A fuzzy outranking method in energy policy planning. Fuzzy Sets and Systems 114, 115–122 (2000)

    Article  Google Scholar 

  30. Geem, Z.W., Kim, J.H., Loganathan, G.V.: A new heuristic optimization algorithm: harmony search. Simulation 76, 60–68 (2001)

    Article  Google Scholar 

  31. Kim, J.H., Geem, Z.W., Kim, E.S.: Parameter estimation of the nonlinear Muskingum model using harmony search. Journal of the American Water Resources Association 37, 1131–1138 (2001)

    Article  Google Scholar 

  32. Paik, K., Kim, J.H., Kim, H.S., Lee, D.R.: A conceptual rainfall-runoff model considering seasonal variation. Hydrological Processes 19, 3837–3850 (2005)

    Article  Google Scholar 

  33. Geem, Z.W.: Optimal cost design of water distribution networks using harmony search. Engineering Optimization 38, 259–280 (2006)

    Article  Google Scholar 

  34. Ayvaz, T.: Simultaneous determination of aquifer parameters and zone structures with fuzzy c-means clustering and meta-heuristic harmony search algorithm. Advances in Water Resources 30, 2326–2338 (2007)

    Article  Google Scholar 

  35. Vasebi, A., Fesanghary, M., Bathaee, S.M.T.: Combined heat and power economic dispatch by harmony search algorithm. International Journal of Electrical Power & Energy Systems 29, 713–719 (2007)

    Article  Google Scholar 

  36. Degertekin, S.O.: Optimum design of steel frames using harmony search algorithm. Struct. Multidisc. Optim. 36, 393–401 (2008)

    Article  Google Scholar 

  37. Lee, K.S., Geem, Z.W.: A new structural optimization method based on the harmony search algorithm. Computers and Structures 82, 781–798 (2004)

    Article  Google Scholar 

  38. Lee, K.S., Geem, Z.W.: A new meta-heuristic algorithm for continuous engineering optimization: harmony search theory and practice. Computational Methods in Applied Mechanical Engineering 194, 3902–3933 (2005)

    Article  MATH  Google Scholar 

  39. Lee, K.S., Geem, Z.W., Lee, S.H., Bae, K.W.: The harmony search heuristic algorithm for discrete structural optimization. Engineering Optimization 37, 663–684 (2005)

    Article  MathSciNet  Google Scholar 

  40. Central Bank of Turkey (CBT) (2007) (accessed December 11, 2008) (in Turkish), http://www.tcmb.gov.tr

  41. General Directorate of Turkish Highways (GDTH), Annual statistics of Turkish highways (2005) (in Turkish) (accessed December 11, 2008), http://www.kgm.gov.tr

Download references

Author information

Authors and Affiliations

  1. Department of Civil Engineering, Pamukkale University, Denizli, Turkey

    Halim Ceylan & Huseyin Ceylan

Authors
  1. Halim Ceylan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Huseyin Ceylan
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Westat, Rockville, MD, USA

    Zong Woo Geem

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Ceylan, H., Ceylan, H. (2009). Harmony Search Algorithm for Transport Energy Demand Modeling. In: Geem, Z.W. (eds) Music-Inspired Harmony Search Algorithm. Studies in Computational Intelligence, vol 191. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00185-7_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-00185-7_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-00184-0

  • Online ISBN: 978-3-642-00185-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation