A novel facility location problem for taxi hailing platforms: A two-stage neighborhood search heuristic approach

Abstract

Purpose

Motivated by a problem in the context of DiDi Travel, the biggest taxi hailing platform in China, the purpose of this paper is to propose a novel facility location problem, specifically, the single source capacitated facility location problem with regional demand and time constraints, to help improve overall transportation efficiency and cost.

Design/methodology/approach

This study develops a mathematical programming model, considering regional demand and time constraints. A novel two-stage neighborhood search heuristic algorithm is proposed and applied to solve instances based on data sets published by DiDi Travel.

Findings

The results of this study show that the model is adequate since new characteristics of demand can be deduced from large vehicle trajectory data sets. The proposed algorithm is effective and efficient on small and medium as well as large instances. The research also solves and presents a real instance in the urban area of Chengdu, China, with up to 30 facilities and demand deduced from 16m taxi trajectory data records covering around 16,000 drivers.

Research limitations/implications

This study examines an offline and single-period case of the problem. It does not consider multi-period or online cases with uncertainties, where decision makers need to dynamically remove out-of-service stations and add other stations to the selected group.

Originality/value

Prior studies have been quite limited. They have not yet considered demand in the form of vehicle trajectory data in facility location problems. This study takes into account new characteristics of demand, regional and time constrained, and proposes a new variant and its solution approach.

Citation

Ma, H., Shen, N., Zhu, J. and Deng, M. (2020), "A novel facility location problem for taxi hailing platforms: A two-stage neighborhood search heuristic approach", Industrial Management & Data Systems, Vol. 120 No. 3, pp. 526-546. https://doi.org/10.1108/IMDS-07-2019-0380