标题： 运输网络增长中直接性与覆盖范围之间的权衡 显示英文标题

标题： The Trade-Off between Directness and Coverage in Transport Network Growth

摘要： 设计空间网络，如交通网络，通常涉及如何通过一组链接最佳地连接一组位置的问题。 在实践中，以一种有助于网络在增长过程中早期发挥作用的方式对链接进行排序可能是至关重要的，例如在自行车网络中。 然而，不清楚不同的增长过程如何实现这种早期功能结构。 在这里，我们系统地研究了连通平面网络的增长，量化了增长网络结构的功能性。 我们比较了随机增长与各种贪婪和人工设计的、手动增长策略。 我们通过直接性和覆盖率的基本性能指标来评估我们的结果，发现它们之间存在非平凡的权衡。 在两个指标上，人工策略都优于贪婪策略，而随机策略表现最差，并且不太可能是帕累托有效的。 基于中心性的贪婪策略在直接性方面表现最好，但在覆盖率方面比随机策略更差，而基于覆盖率的贪婪策略可以尽可能快地实现最大全局覆盖率，但在直接性方面表现与随机策略一样差。 基于直接性的贪婪策略会陷入局部最优陷阱。 这些结果适用于多种简化的城市交通网络拓扑结构。 我们的见解对于链接添加顺序在空间网络中很重要的应用至关重要，例如在城市或区域交通网络设计问题中。 显示英文摘要

摘要： Designing spatial networks, such as transport networks, commonly deals with the problem of how to best connect a set of locations through a set of links. In practice, it can be crucial to order the implementation of the links in a way that facilitates early functioning of the network during growth, like in bicycle networks. However, it is unclear how this early functional structure can be achieved by different growth processes. Here, we systematically study the growth of connected planar networks, quantifying functionality of the growing network structure. We compare random growth with various greedy and human-designed, manual growth strategies. We evaluate our results via the fundamental performance metrics of directness and coverage, finding non-trivial trade-offs between them. Manual strategies fare better than greedy strategies on both metrics, while random strategies perform worst and are unlikely to be Pareto efficient. Centrality-based greedy strategies tend to perform best for directness but are worse than random strategies for coverage, while coverage-based greedy strategies can achieve maximum global coverage as fast as possible but perform as poorly for directness as random strategies. Directness-based greedy strategies get stuck in local optimum traps. These results hold for a number of stylized urban transport network topologies. Our insights are crucial for applications where the order in which links are added to a spatial network is important, such as in urban or regional transport network design problems.