The Influence of Agent Models on the Complexity of Bus Routing

2026-08-18

AI Summary

研究了公交线路规划中不同代理模型对问题复杂性的影响，通过改变目标函数和代理步行成本模型，探讨了在树状网络结构下的计算难度。

Abstract

In bus routing, the task is to plan a bus route in a network with several agents, each of whom wants to travel from a starting point to a destination. A bus route should account for several factors, including agents' cost for reaching the bus stops, their travel time, or the energy consumption of the buses. We study the complexity of several variants of this problem, focusing on how the objective function and the models for agents' walking costs influence the problem complexity. After observing that even the simplest agent cost model leads to hardness on general networks, we consider networks with tree structure. Our main findings are as follows. First, allowing agent-specific cost models leads to hardness even on extremely limited trees such as stars. Second, consistent agent models (where agents differ only in their starting points and destinations) make the problem easier in some cases. Finally, allowing agents to choose between using the bus and walking directly can make the problem considerably harder. Most of our hardness results show not only classical NP-hardness but also parameterized intractability for the natural parameter $k$, the number of bus stops.

Problem

• bus routing
• complexity
• agent models
• objective function
• walking costs

Innovation

• agent-specific cost models
• consistent agent models
• parameterized intractability
• bus and walking choice