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多层网络增长中的帕累托最优。

Pareto Optimality in Multilayer Network Growth.

机构信息

School of Mathematical Sciences, Queen Mary University of London, Mile End Road, E1 4NS, London, United Kingdom.

Scuola Superiore di Catania, Università di Catania, Via Valdisavoia 9, 95125, Catania, Italy.

出版信息

Phys Rev Lett. 2018 Sep 21;121(12):128302. doi: 10.1103/PhysRevLett.121.128302.

Abstract

We model the formation of multilayer transportation networks as a multiobjective optimization process, where service providers compete for passengers, and the creation of routes is determined by a multiobjective cost function encoding a trade-off between efficiency and competition. The resulting model reproduces well real-world systems as diverse as airplane, train, and bus networks, thus suggesting that such systems are indeed compatible with the proposed local optimization mechanisms. In the specific case of airline transportation systems, we show that the networks of routes operated by each company are placed very close to the theoretical Pareto front in the efficiency-competition plane, and that most of the largest carriers of a continent belong to the corresponding Pareto front. Our results shed light on the fundamental role played by multiobjective optimization principles in shaping the structure of large-scale multilayer transportation systems, and provide novel insights to service providers on the strategies for the smart selection of novel routes.

摘要

我们将多层交通网络的形成建模为一个多目标优化过程,其中服务提供商竞争乘客,而路线的创建则由一个多目标成本函数决定,该函数在效率和竞争之间进行权衡。所得到的模型很好地再现了多样化的真实世界系统,如飞机、火车和公共汽车网络,这表明这些系统确实与所提出的局部优化机制相兼容。在航空公司运输系统的具体情况下,我们表明,每家公司运营的航线网络在效率-竞争平面上非常接近理论帕累托前沿,而且一个大陆的大多数最大航空公司都属于相应的帕累托前沿。我们的研究结果揭示了多目标优化原则在塑造大规模多层交通系统结构方面所起的基本作用,并为服务提供商提供了有关智能选择新航线的策略的新见解。

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