Roads Development Optimization for All-Season Service Accessibility Improvement in Rural Nepal Using a Novel Cost-Time Model and Evolutionary Algorithm
Existing methods of prioritizing rural roads for construction in hilly and mountainous settings require expensive data collection or major simplifications of ground conditions. Traditional social surplus based-methods favor economic and political decision criteria over social criteria, despite...
| Main Authors: | , , |
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| Format: | Working Paper |
| Language: | English |
| Published: |
World Bank, Washington, DC
2021
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| Subjects: | |
| Online Access: | http://documents.worldbank.org/curated/en/486171611677840463/Roads-Development-Optimization-for-All-Season-Service-Accessibility-Improvement-in-Rural-Nepal-Using-a-Novel-Cost-Time-Model-and-Evolutionary-Algorithm http://hdl.handle.net/10986/35073 |
| Summary: | Existing methods of prioritizing rural roads for construction
in hilly and mountainous settings require expensive
data collection or major simplifications of ground conditions.
Traditional social surplus based-methods favor
economic and political decision criteria over social criteria,
despite evidence of the latter’s importance, and struggle
to scale beyond major roads to feeder roads, forcing local
governments with limited capacity to adopt ad-hoc alternative
criteria. Using roads proposed for construction in
Nepal’s remote Karnali province, this paper develops a
scalable method to prioritize these roads for inclusion in
construction plans with the aim of optimizing potential
accessibility improvements to specified services in dry and
monsoon seasons—within Karnali’s infrastructure budget
constraints. Road-specific improvements in accessibility to
services are measured by estimating accessibility changes
resulting from each proposed road within a multimodal
accessibility model. In this paper, walking across Karnali’s
mountainous, high-elevation terrain is incorporated as a
primary modality—a rarity in related accessibility literature.
These improvements are implemented within heuristic and
integer-linear programming optimization models. Optimization-determined
solutions were calculated within a day,
and substantially outperformed the actual roads selected
by Karnali’s provincial government in terms of accessibility,
efficiency, and political economy |
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