Designing zonal-based flexible bus services under stochastic demand

TL;DR

This paper presents a stochastic optimization model for designing flexible zonal bus services that adapt to demand variability, aiming to reduce costs while maintaining service quality, demonstrated through real-world data application.

Contribution

It introduces a two-stage stochastic programming approach for zonal-based flexible bus services considering demand stochasticity and reliability, a novel integration for cost-effective transit planning.

Findings

ZBFBS reduces operational costs compared to fixed-route services.

Demand volume and detour time reliabilities improve service quality.

Model effectively adapts to real-world demand variability in Chengdu, China.

Abstract

In this paper, we develop a zonal-based flexible bus services (ZBFBS) by considering both passenger demands spatial (origin-destination or OD) and volume stochastic variations. Service requests are grouped by zonal OD pairs and number of passengers per request, and aggregated into demand categories which follow certain probability distributions. A two-stage stochastic program is formulated to minimize the expected operating cost of ZBFBS, in which the zonal visit sequences of vehicles are determined in Stage-1, whereas in Stage-2, service requests are assigned to either regular routes determined in Stage-1 or ad hoc services that incur additional costs. Demand volume reliability and detour time reliability are introduced to ensure quality of the services and separate the problem into two phases for efficient solutions. In phase-1, given the reliability requirements, we minimize the cost of operating the regular services. In phase-2, we optimize the passenger assignment to vehicles to minimize the expected ad hoc service cost. The reliabilities are then optimized by a gradient-based approach to minimize the sum of the regular service operating cost and expected ad hoc service cost. We conduct numerical studies on vehicle capacity, detour time limit and demand volume to demonstrate the potential of ZBFBS, and apply the model to Chengdu, China, based on real data to illustrate its applicability.