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Transport Demand Management in Turkey: A Genetic Algorithm Approach

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  • Soner Haldenbilen
  • Halim Ceylan

Abstract

This article proposes new models for estimating transport demand using a genetic algorithm (GA) approach. Based on population, gross national product and number of vehicles, four forms of the genetic algorithm transport planning (GATP) model are developed -- one exponential and the others taking quadratic forms -- and applied to Turkey. The best fit models in terms of minimum total average relative errors in the test period are selected for future estimation. Demand management strategies are proposed based on three scenarios: restricting private car use, restricting truck use and the simultaneous management of private car use and goods movement. Results show that the GATP model may be used to estimate transport demand in terms of passenger-kilometers traveled (pass-km), vehicle-kilometers traveled (veh-km) and ton-kilometers completed (ton-km). Results also show that the third scenario -- simultaneous restrictions on private car use and goods movement -- could reduce total veh-km by about 35% by 2025 in this study of Turkish rural roads.

Suggested Citation

  • Soner Haldenbilen & Halim Ceylan, 2005. "Transport Demand Management in Turkey: A Genetic Algorithm Approach," Transportation Planning and Technology, Taylor & Francis Journals, vol. 28(6), pages 403-426, August.
    • Handle: RePEc:taf:transp:v:28:y:2005:i:6:p:403-426
    DOI: 10.1080/03081060500515507
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    Cited by:

    1. Aytekin, Ahmet & Korucuk, Selçuk & Görçün, Ömer Faruk, 2024. "Determining the factors affecting transportation demand management and selecting the best strategy: A case study," Transport Policy, Elsevier, vol. 146(C), pages 150-166.
    2. Ozan, Cenk & Haldenbilen, Soner & Ceylan, Halim, 2011. "Estimating emissions on vehicular traffic based on projected energy and transport demand on rural roads: Policies for reducing air pollutant emissions and energy consumption," Energy Policy, Elsevier, vol. 39(5), pages 2542-2549, May.

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