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Optimisation of rural roads planning based on multi-modal travel: a multi-service accessibility study in Nepal’s remote Karnali Province

Author

Listed:
  • Andries M. Heyns

    (Hanken School of Economics
    University of Alabama)

  • Robert Banick

    (World Bank, Poverty and Equity Global Practice)

Abstract

The traditional aim in transportation planning is to maximise gains associated with vehicular travel distances or times, indirectly prioritising populations that live near existing or proposed roads—remote populations that first require hours of walking to reach roads are overlooked. In this paper, rural roads optimisation is performed using a new model that estimates proposed roads’ accessibility gains, considering reductions in vehicular travel time and reductions in walking time required by remote populations to reach them. This ensures that even the most remote populations that may benefit from new roads are included in their evaluation. When presented with a large number of proposed roads and the requirement of determining a plan within a suitable budget, it is often infeasible to construct all proposed roads. In such instances, subsets of well-performing road-combinations that are evaluated with respect to multiple objectives need to be identified for analysis and comparison–for which multi-objective optimisation approaches can be employed. Traditional optimisation approaches return a small number of road-combination plans only, limited to user-specified budget levels and objective weight sets. This paper presents an innovative heuristic solution approach that overcomes such limitations by returning thousands of well-performing solutions scattered across a budget span, and not limited in number to user-specified objective weight sets at fixed budget levels. The heuristic is employed along with a more traditional weighted-sum integer-linear programming approach to determine high-quality road-combination plans selected from 92 roads recently proposed for construction in Nepal’s remote Karnali province. Using these two approaches with inputs from the new multi-modal accessibility model, it is illustrated how rural roads planning can be performed to the benefit of rural populations regardless of their proximity to roads. New planning and analysis benefits of the heuristic are demonstrated by comparing its solutions to those determined by the weighted-sum approach, providing a level of detail and sophistication not previously possible for rural roads planning and analysis.

Suggested Citation

  • Andries M. Heyns & Robert Banick, 2024. "Optimisation of rural roads planning based on multi-modal travel: a multi-service accessibility study in Nepal’s remote Karnali Province," Transportation, Springer, vol. 51(2), pages 567-613, April.
  • Handle: RePEc:kap:transp:v:51:y:2024:i:2:d:10.1007_s11116-022-10343-3
    DOI: 10.1007/s11116-022-10343-3
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    References listed on IDEAS

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    1. Anjali Adukia & Sam Asher & Paul Novosad, 2020. "Educational Investment Responses to Economic Opportunity: Evidence from Indian Road Construction," American Economic Journal: Applied Economics, American Economic Association, vol. 12(1), pages 348-376, January.
    2. Murawski, Lisa & Church, Richard L., 2009. "Improving accessibility to rural health services: The maximal covering network improvement problem," Socio-Economic Planning Sciences, Elsevier, vol. 43(2), pages 102-110, June.
    3. Machairas, Vasileios & Tsangrassoulis, Aris & Axarli, Kleo, 2014. "Algorithms for optimization of building design: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 31(C), pages 101-112.
    4. Tanser, Frank & Gijsbertsen, Brice & Herbst, Kobus, 2006. "Modelling and understanding primary health care accessibility and utilization in rural South Africa: An exploration using a geographical information system," Social Science & Medicine, Elsevier, vol. 63(3), pages 691-705, August.
    5. Marcel Fafchamps & Forhad Shilpi, 2003. "The spatial division of labour in Nepal," Journal of Development Studies, Taylor & Francis Journals, vol. 39(6), pages 23-66.
    6. Sapkota, Jeet Bahadur, 2018. "Access to infrastructure and human wellbeing: evidence from rural Nepal," MPRA Paper 106094, University Library of Munich, Germany.
    7. Banick,Robert Steven & Kawasoe,Yasuhiro, 2019. "Measuring Inequality of Access : Modeling Physical Remoteness in Nepal," Policy Research Working Paper Series 8966, The World Bank.
    8. Paul J. Densham & Gerard Rushton, 1992. "A More Efficient Heuristic For Solving Large P‐Median Problems," Papers in Regional Science, Wiley Blackwell, vol. 71(3), pages 307-329, July.
    9. ReVelle, C. S. & Eiselt, H. A., 2005. "Location analysis: A synthesis and survey," European Journal of Operational Research, Elsevier, vol. 165(1), pages 1-19, August.
    10. Binswanger, Hans P. & Khandker, Shahidur R. & Rosenzweig, Mark R., 1993. "How infrastructure and financial institutions affect agricultural output and investment in India," Journal of Development Economics, Elsevier, vol. 41(2), pages 337-366, August.
    11. Devkota, Bhuwan & Dudycha, Douglas & Andrey, Jean, 2012. "Planning for non-motorized travel in rural Nepal: a role for geographic information systems," Journal of Transport Geography, Elsevier, vol. 24(C), pages 282-291.
    12. Michael B. Teitz & Polly Bart, 1968. "Heuristic Methods for Estimating the Generalized Vertex Median of a Weighted Graph," Operations Research, INFORMS, vol. 16(5), pages 955-961, October.
    13. Luc Christiaensen & Lionel Demery & Stefano Paternostro, 2003. "Reforms, Remoteness and Risk in Africa: Understanding Inequality and Poverty during the 1990s," WIDER Working Paper Series DP2003-70, World Institute for Development Economic Research (UNU-WIDER).
    14. Changxi Ma & Cunrui Ma & Qing Ye & Ruichun He & Jieyan Song, 2014. "An Improved Genetic Algorithm for the Large-Scale Rural Highway Network Layout," Mathematical Problems in Engineering, Hindawi, vol. 2014, pages 1-6, April.
    15. Jerry Lebo & Dieter Schelling, 2001. "Design and Appraisal of Rural Transport Infrastructure : Ensuring Basic Access for Rural Communities," World Bank Publications - Books, The World Bank Group, number 13911, December.
    16. Shrestha, Jagat K. & Benta, Agostinho & Lopes, Rui B. & Lopes, Nuno, 2014. "A multi-objective analysis of a rural road network problem in the hilly regions of Nepal," Transportation Research Part A: Policy and Practice, Elsevier, vol. 64(C), pages 43-53.
    17. Jacoby, Hanan C, 2000. "Access to Markets and the Benefits of Rural Roads," Economic Journal, Royal Economic Society, vol. 110(465), pages 713-737, July.
    18. Jeet Bahadur Sapkota, 2018. "Access to infrastructure and human well-being: evidence from rural Nepal," Development in Practice, Taylor & Francis Journals, vol. 28(2), pages 182-194, February.
    19. Páez, Antonio & Scott, Darren M. & Morency, Catherine, 2012. "Measuring accessibility: positive and normative implementations of various accessibility indicators," Journal of Transport Geography, Elsevier, vol. 25(C), pages 141-153.
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