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Optimization Framework for ASIAN and National Road Networks in Lao PDR Using the Stochastic Markov Model

Souvikhane Hanpasith, Felix Obunguta, Kotaro Sasai, Kiyoyuki Kaito

Abstract


Developing effective road network management is crucial for the socioeconomic development of developing countries, particularly the Lao People’s Democratic Republic (Lao PDR or Laos). The current road maintenance system in Lao PDR uses a traditional reactive maintenance approach, addressing road deterioration only after the condition reaches a critical state. This study proposes a stochastic Markov Decision Process (MDP) framework to enhance traditional road management practices. The proposed MDP framework shifts from a conventional reactive to a proactive strategy by considering probabilistic pavement performance and optimally allocating funding to rapidly deteriorating sections. This study enables decision-makers to determine the optimal intervention strategies based on different scenarios. The comparison of the ASIAN Road network, high technical design and construction, and the National Road network, standard technical design and construction, in different scenarios provides a workable framework for maintaining Laos, and other developing countries, road condition despite limited resources and sustainable development concerns. This comprehensive framework includes estimating deterioration rates, defining policies, conducting life-cycle cost (LCC) analysis, and determining optimal strategies that minimize LCC subject to financial and performance constraints. This study highlights significant improvements in decision-making, particularly in resource allocation, by creating innovative and preventive approaches that enhance the efficiency of road management systems and ensure sustainable maintenance practices in Lao PDR.

 

Doi: 10.28991/CEJ-2025-011-05-023

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Keywords


Optimum Road Intervention Strategy; Markov Decision Process; Laos Road Management Systems; Life-Cycle Cost Analysis.

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Full Text: PDF

DOI: 10.28991/CEJ-2025-011-05-023

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Copyright (c) 2025 Souvikhane Hanpasith

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