On the public citation graph

Multi-Objective Dispatching Strategy of Autonomous Service Vehicles in Ride-Hailing Based on an Interpretable Prediction Model

https://doi.org/10.2139/ssrn.4669773
0 signed · 51 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/s00500-021-06386-wopenalex-extracted
An application of extended NSGA-II in interval valued multi-objective scheduling problem of crews
inferredcites →https://doi.org/10.1007/s10489-018-1181-7openalex-extracted
A multivariate short-term traffic flow forecasting method based on wavelet analysis and seasonal time series
inferredcites →https://doi.org/10.1007/s10489-022-03966-7openalex-extracted
Urban ride-hailing demand prediction with multi-view information fusion deep learning framework
inferredcites →https://doi.org/10.1007/s11116-022-10356-yopenalex-extracted
Traditional taxi, e-hailing or ride-hailing? A GSEM approach to exploring service adoption patterns
inferredcites →https://doi.org/10.1016/j.aap.2023.107072openalex-extracted
A proactive crash risk prediction framework for lane-changing behavior incorporating individual driving styles
inferredcites →https://doi.org/10.1016/j.cie.2019.02.032openalex-extracted
A column generation algorithm for vehicle scheduling and routing problems
inferredcites →https://doi.org/10.1016/j.clsr.2019.02.005openalex-extracted
A reflection on the taxi reform in China: Innovation vs. Tradition
inferredcites →https://doi.org/10.1016/j.comnet.2020.107530openalex-extracted
Machine Learning-based traffic prediction models for Intelligent Transportation Systems
inferredcites →https://doi.org/10.1016/j.cor.2022.105698openalex-extracted
A novel multi-objective green vehicle routing and scheduling model with stochastic demand, supply, and variable travel times
inferredcites →https://doi.org/10.1016/j.ejor.2020.01.033openalex-extracted
Approximate dynamic programming for planning a ride-hailing system using autonomous fleets of electric vehicles
inferredcites →https://doi.org/10.1016/j.ejor.2020.12.021openalex-extracted
Metaheuristics for the online printing shop scheduling problem
inferredcites →https://doi.org/10.1016/j.ejor.2021.07.054openalex-extracted
Vehicle dispatching plan for minimizing passenger waiting time in a corridor with buses of different sizes: Model formulation and solution approaches
inferredcites →https://doi.org/10.1016/j.ejor.2021.08.014openalex-extracted
The parallel drone scheduling problem with multiple drones and vehicles
inferredcites →https://doi.org/10.1016/j.ejor.2021.10.012openalex-extracted
On the Shapley value of liability games
inferredcites →https://doi.org/10.1016/j.ejor.2022.02.021openalex-extracted
Interrelated trips in the rural dial-a-ride problem with autonomous vehicles
inferredcites →https://doi.org/10.1016/j.ejor.2022.04.035openalex-extracted
Modelling and analysis of online ride-sharing platforms – A sustainability perspective
inferredcites →https://doi.org/10.1016/j.ejor.2022.06.050openalex-extracted
Multi-depot electric vehicle scheduling in in-plant production logistics considering non-linear charging models
inferredcites →https://doi.org/10.1016/j.ejor.2022.07.017openalex-extracted
An exact approach for the multi-depot electric bus scheduling problem with time windows
inferredcites →https://doi.org/10.1016/j.ijpe.2021.108301openalex-extracted
On-demand ride-hailing platforms in competition with the taxi industry: Pricing strategies and government supervision
inferredcites →https://doi.org/10.1016/j.ins.2020.05.082openalex-extracted
An improved MOEA/D algorithm with an adaptive evolutionary strategy
inferredcites →https://doi.org/10.1016/j.neucom.2005.12.132openalex-extracted
CATS benchmark time series prediction by Kalman smoother with cross-validated noise density
inferredcites →https://doi.org/10.1016/j.neucom.2023.01.009openalex-extracted
Δ free -LSTM: An error distribution free deep learning for short-term traffic flow forecasting
inferredcites →https://doi.org/10.1016/j.trb.2016.11.004openalex-extracted
A statistical method for estimating predictable differences between daily traffic flow profiles
inferredcites →https://doi.org/10.1016/j.trb.2019.07.009openalex-extracted
Ridesourcing systems: A framework and review
inferredcites →https://doi.org/10.1016/j.trb.2021.05.015openalex-extracted
Robust matching-integrated vehicle rebalancing in ride-hailing system with uncertain demand
inferredcites →https://doi.org/10.1016/j.trc.2021.103156openalex-extracted
Efficient dispatching for on-demand ride services: Systematic optimization via Monte-Carlo tree search
inferredcites →https://doi.org/10.1016/j.tre.2021.102530openalex-extracted
Vehicle scheduling for rental-with-driver services
inferredcites →https://doi.org/10.1016/j.tre.2022.102694openalex-extracted
Deep dispatching: A deep reinforcement learning approach for vehicle dispatching on online ride-hailing platform
inferredcites →https://doi.org/10.1038/s41467-022-31911-2openalex-extracted
Forecasting the evolution of fast-changing transportation networks using machine learning
inferredcites →https://doi.org/10.1063/5.0129721openalex-extracted
Short duration traffic flow prediction using kalman filtering
inferredcites →https://doi.org/10.1080/00207543.2021.1871675openalex-extracted
Multi-dimensional spatiotemporal demand forecasting and service vehicle dispatching for online car-hailing platforms
inferredcites →https://doi.org/10.1080/00207543.2021.1919780openalex-extracted
Level-based multi-objective particle swarm optimizer for integrated production scheduling and vehicle routing decision with inventory holding, delivery, and tardiness costs
inferredcites →https://doi.org/10.1080/08839514.2021.2018643openalex-extracted
Prediction in Traffic Accident Duration Based on Heterogeneous Ensemble Learning
inferredcites →https://doi.org/10.1109/4235.797969openalex-extracted
Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach
inferredcites →https://doi.org/10.1109/4235.996017openalex-extracted
A fast and elitist multiobjective genetic algorithm: NSGA-II
inferredcites →https://doi.org/10.1109/icdm.2019.00129openalex-extracted
Deep Reinforcement Learning for Multi-driver Vehicle Dispatching and Repositioning Problem
inferredcites →https://doi.org/10.1109/icpeca51329.2021.9362615openalex-extracted
Research on Vehicle Dispatch Problem Based on Kuhn-Munkres and Reinforcement Learning Algorithm
inferredcites →https://doi.org/10.1109/jiot.2017.2716114openalex-extracted
Data Driven Congestion Trends Prediction of Urban Transportation
inferredcites →https://doi.org/10.1109/tits.2019.2948790openalex-extracted
Spatio-Temporal Ensemble Method for Car-Hailing Demand Prediction
inferredcites →https://doi.org/10.1109/tits.2021.3094659openalex-extracted
A Short-Term Traffic Flow Prediction Model Based on an Improved Gate Recurrent Unit Neural Network
inferredcites →https://doi.org/10.1109/tits.2021.3119662openalex-extracted
Deep Reinforcement Learning With Graph Representation for Vehicle Repositioning
inferredcites →https://doi.org/10.1109/tits.2021.3131248openalex-extracted
A Diverse Ensemble Deep Learning Method for Short-Term Traffic Flow Prediction Based on Spatiotemporal Correlations
inferredcites →https://doi.org/10.1109/tits.2023.3237387openalex-extracted
Temporal Data Scheduling in Internet of Vehicles Using an Improved Decomposition-Based Multi-Objective Evolutionary Algorithm
inferredcites →https://doi.org/10.1109/tnse.2020.2992931openalex-extracted
The Framework of Increasing Drivers’ Income on the Online Taxi Platforms
inferredcites →https://doi.org/10.1142/s0218001422590091openalex-extracted
An Improved A-Star Algorithm for Complete Coverage Path Planning of Unmanned Ships
inferredcites →https://doi.org/10.24963/ijcai.2019/264openalex-extracted
Graph WaveNet for Deep Spatial-Temporal Graph Modeling
inferredcites →https://doi.org/10.3390/app10248933openalex-extracted
Intelligent Total Transportation Management System for Future Smart Cities
inferredcites →https://doi.org/10.3390/ijerph19052925openalex-extracted
Predicting and Analyzing Road Traffic Injury Severity Using Boosting-Based Ensemble Learning Models with SHAPley Additive exPlanations
inferredcites →https://doi.org/10.3390/su14074164openalex-extracted
Traffic Flow Prediction: An Intelligent Scheme for Forecasting Traffic Flow Using Air Pollution Data in Smart Cities with Bagging Ensemble
inferredcites →https://doi.org/10.48550/arxiv.1707.01926openalex-extracted
Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting
inferredcites →https://doi.org/10.48550/arxiv.2304.06639openalex-extracted
Towards Prototyping Driverless Vehicle Behaviors, City Design, and Policies Simultaneously
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.