A simulation-based optimisation approach for identifying key determinants for sustainable transportation planning
R Sayyadi, A Awasthi - … Journal of Systems Science: Operations & …, 2018 - Taylor & Francis
Sustainable transportation planning is vital to manage resources effectively and minimise air
pollution, noise and congestion in cities. In this paper, we present a simulation-based …
pollution, noise and congestion in cities. In this paper, we present a simulation-based …
A data-driven discrete simulation-based optimization algorithm for car-sharing service design
This paper formulates a discrete simulation-based optimization (SO) algorithm for a family of
large-scale car-sharing service design problems. We focus on the profit-optimal assignment …
large-scale car-sharing service design problems. We focus on the profit-optimal assignment …
A Bayesian clustering ensemble Gaussian process model for network-wide traffic flow clustering and prediction
Traffic flow prediction is an essential component in intelligent transportation systems.
Recently, there has been a notable trend in applying machine learning models, especially …
Recently, there has been a notable trend in applying machine learning models, especially …
[图书][B] Informed Urban transport systems: Classic and emerging mobility methods toward smart cities
J Chow - 2018 - books.google.com
Informed Urban Transport Systems examines how information gathered from new
technologies can be used for optimal planning and operation in urban settings …
technologies can be used for optimal planning and operation in urban settings …
An equilibrium approach for compensating public–private partnership concessionaires for reduced tolls during roadway maintenance
S Mamdoohi, E Miller-Hooks, J Gifford - Transportation Research Part A …, 2023 - Elsevier
This study considers the possibility of exploiting excess capacity along concurrent tolled
roadway facilities operating in a public–private partnership for the purpose of alleviating …
roadway facilities operating in a public–private partnership for the purpose of alleviating …
Integrating probabilistic tensor factorization with Bayesian supervised learning for dynamic ridesharing pattern analysis
In the era of transportation big data, the analysis of mobility patterns generally involves large
quantities of datasets with high-dimensional variables recording individual travelers' …
quantities of datasets with high-dimensional variables recording individual travelers' …
Time-of-day vehicle mileage fees for congestion mitigation and revenue generation: A simulation-based optimization method and its real-world application
Congestion pricing of a large-scale network is characterized by expensive-to-evaluate
objective functions without closed forms. This paper further enhances a computationally …
objective functions without closed forms. This paper further enhances a computationally …
Simulation-based optimization of large-scale dedicated bus lanes allocation: Using efficient machine learning models as surrogates
Abstract Dedicated Bus Lanes (DBLs) have been implemented in many cities to boost
buses' reliability and to alleviate traffic congestions. However, how to correctly allocate DBLs …
buses' reliability and to alleviate traffic congestions. However, how to correctly allocate DBLs …
A simulation-based model for continuous network design problem using Bayesian optimization
This paper investigates the continuous network design problem (CNDP) and proposes a
simulation-based bi-level model and solution framework based on Bayesian optimization. In …
simulation-based bi-level model and solution framework based on Bayesian optimization. In …
Simulation-based analysis of second-best multimodal network capacity
Modeling the capacity of a transportation system ought to be an essential task for assessing
the level of service of urban transportation networks. Compared to the maximum traffic …
the level of service of urban transportation networks. Compared to the maximum traffic …