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.

交通规划的传统目标是最大限度地提高与车辆行驶距离或时间相关的收益，间接优先考虑居住在现有或拟建道路附近的人群，而忽略了首先需要数小时步行才能到达道路的偏远人群。在本文中，农村道路优化是使用一种新模型进行的，该模型估计拟议道路的可达性增益，考虑到车辆出行时间的减少和减少偏远人群到达他们所需的步行时间。这确保了即使是可能从新道路中受益的最偏远人口也被纳入他们的评估中。当提出大量拟建道路并要求在合适的预算内确定计划时，通常无法建造所有拟建道路。在这种情况下，需要确定针对多个目标进行评估的性能良好的道路组合子集以进行分析和比较——可以采用多目标优化方法。传统的优化方法只返回少量的道路组合计划，仅限于用户指定的预算水平和目标权重集。本文提出了一种创新的启发式解决方案方法，该方法通过返回分散在预算范围内的数千个性能良好的解决方案来克服这些限制，并且不限于在固定预算水平上用户指定的目标权重集。启发式与更传统的加权和整数线性规划方法一起使用，以确定从最近提议在尼泊尔偏远的卡纳利省建设的 92 条道路中选择的高质量道路组合计划。使用这两种方法以及来自新的多模式可达性模型的输入，它说明了如何执行农村道路规划以造福农村人口，而不管他们是否靠近道路。