Article
Economics
Xiaolei Wang, Jun Wang, Lei Guo, Wei Liu, Xiaoning Zhang
Summary: A new modeling approach for ridesharing user equilibrium (RUE) was proposed, which transforms the problem into a convex programming problem by redefining feasible driver trajectories and ridesharing market equilibrium conditions. The algorithm effectively avoids path enumeration and can be implemented on large networks, with theoretical analysis and numerical demonstrations on the impact of problem size on computational efficiency.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2021)
Article
Management
Muqing Du, Heqing Tan, Anthony Chen
Summary: This paper explores a novel step size determination scheme, the Barzilai-Borwein step size, and applies it to solving the stochastic user equilibrium problem. Experimental results demonstrate that the BB step size outperforms current step size strategies in terms of computational efficiency and robustness.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Economics
Ruqing Huang, Lee D. Han, Zhongxiang Huang
Summary: This paper presents an unconventional equilibrium flow model to analyze travelers' route choice behavior, using path residual capacity as the quantity signal. The proposed model and solution algorithm are shown to be feasible and effective, and can capture route choice behaviors that have not been modeled in previous studies.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2022)
Article
Economics
Terry L. Friesz, Ke Han, Amir Bagherzadeh
Summary: This paper presents sufficient conditions for convergence of projection and fixed-point algorithms used to compute dynamic user equilibrium with elastic travel demand, without the need for strongly monotone increasing path delay operators. Instead, weakly monotone increasing path delay operators and strongly monotone decreasing inverse demand functions are assumed. The Lipschitz continuity of path delay is a mild regularity condition, allowing for convergence even with nonmonotone delay operators under certain conditions.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2021)
Article
Economics
Tongfei Li, Min Xu, Huijun Sun, Jie Xiong, Xueping Dou
Summary: In this study, a generalized stochastic user equilibrium model is developed to analyze travelers' mode and route choice behavior in urban traffic systems with ridesharing programs. The proposed model considers travelers' heterogeneity in terms of car ownership and value of time, and their limited perceived information based on the stochastic user equilibrium principle. The decision-making problem of ridesharing compensation is also addressed, aiming to minimize total travel cost and vehicular air pollution emissions. A bi-objective optimization model and two single-objective optimization models are proposed, and a genetic algorithm is used to generate Pareto-optimal solutions. Numerical experiments demonstrate the effectiveness of the proposed model and algorithm in mitigating traffic congestion and pollution emissions.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2023)
Article
Computer Science, Interdisciplinary Applications
Sam O'Neill, Ovidiu Bagdasar, Stuart Berry, Nicolae Popovici, Ramachandran Raja
Summary: This paper presents a method of considering multiple objectives simultaneously in selfish routing of network flow. By manipulating free parameters such as speed limits, the behavior of road users is coerced to reconcile conflicts between multiple objectives. The results show that small parameter adjustments can lead to solutions that Pareto dominate other solutions.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2022)
Article
Computer Science, Interdisciplinary Applications
Xiang Zhang, Steven Travis Waller, Dung-Ying Lin
Summary: This study is the first in the literature to examine the Braess paradox considering parking behavior in the autonomous vehicle (AV) environment and model the network design problem for the autonomous transportation system (NDP-ATS). It shows the existence of two distinct Braess paradoxes in AV traffic networks and develops a bi-level programming model to avoid the deterioration caused by these paradoxes. The results highlight the efficacy of the modeling framework for infrastructure development and policy assessment for AV traffic.
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
(2023)
Article
Transportation Science & Technology
Nam H. Hoang, Manoj Panda, Hai L. Vu, Dong Ngoduy, Hong K. Lo
Summary: This study focuses on a transport network with two types of users, selfish and cooperative. Selfish users aim to minimize their travel time, while cooperative users aim to maximize their class's aggregate throughput or minimize their total travel time. A new framework is proposed to study the route choices and network performance of the two classes of users.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2023)
Article
Economics
Yuki Oyama, Yusuke Hara, Takashi Akamatsu
Summary: This study fills the research gap by establishing a Markovian traffic equilibrium assignment based on the network generalized extreme value (NGEV) model. The study provides the necessary theoretical developments for the NGEV equilibrium assignment, including the formulation and solution under the same path algebra as traditional models. Equivalent optimization formulations are also presented, allowing for efficient solution algorithms. The numerical experiments demonstrate the excellent convergence and complementary relationship of the proposed algorithms.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2022)
Article
Environmental Studies
D. Kang, F. Hu, M. W. Levin
Summary: This study examines the impacts of induced AV trips on the transportation network and proposes a solution algorithm. Test results demonstrate that the use of AVs increases average travel time and allows for the repurposing of parking spaces.
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
(2022)
Article
Energy & Fuels
Quan Yuan, Yujian Ye, Yi Tang, Yuanchang Liu, Goran Strbac
Summary: This paper proposes a novel deep learning based surrogate modeling method for effective modeling and optimization of EV flows and charging demand. Case studies demonstrate that the proposed method outperforms existing methods in both solution accuracy and computational performance. Coordinated spatial optimization of EV flows and charging demand benefits the operation of both TN and PDN.
Article
Engineering, Multidisciplinary
Tomas Potuzak, Frantisek Kolovsky
Summary: This paper describes a technique for predicting traffic flows in individual roads of a road traffic network and presents the parallelization process of the technique, along with the convergence, usability, and speed tests conducted on real road traffic networks.
AIN SHAMS ENGINEERING JOURNAL
(2022)
Article
Computer Science, Artificial Intelligence
Yuji Zou, Jin-Kao Hao, Qinghua Wu
Summary: This article presents an effective heuristic algorithm for the traveling salesman problem with job-times. The algorithm uses a breakout local search method to find high-quality local optimal solutions and incorporates a perturbation procedure to escape local optimum traps. Computational results show that the algorithm outperforms previous methods on benchmark instances.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Thermodynamics
Ze Zhou, Zhitao Liu, Hongye Su, Liyan Zhang
Summary: Dynamic wireless charging technology can alleviate range anxiety and promote the widespread use of electric vehicles. It is important to consider it as a significant charging method in future urban scenarios. This study proposes a planning strategy for the coexistence of static and dynamic charging facilities in order to maximize the comprehensive performance of the power-traffic system.
Article
Management
Zhiyuan Liu, Xinyuan Chen, Jintao Hu, Shuaian Wang, Kai Zhang, Honggang Zhang
Summary: This paper introduces a new parallel computing algorithm to solve the user equilibrium problem. Existing solution algorithms in transportation research can be classified into three categories: link-based, path-based, and origin-based. This paper proposes an alternating direction method of multipliers (ADMM) algorithm, which is different from these categories. It utilizes the origin-based formulation of the problem and eliminates the flow conservation conditions through an augmented Lagrangian function. The network links are grouped into different blocks for the ADMM, and a novel approach is developed for this link grouping problem.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Transportation
Guangchao Wang, Kebo Tong, Anthony Chen, Hang Qi, Xiangdong Xu, Shoufeng Ma
Summary: This study investigates the impacts of the least perceived travel cost on the stochastic user equilibrium problem. The Weibit SUE models with a positive location parameter reduce perception variances route-specifically and resolve the scale insensitivity issue. Numerical results confirm the analytical results and demonstrate the efficiency and robustness of the proposed solution algorithm.
TRANSPORTMETRICA A-TRANSPORT SCIENCE
(2023)
Article
Computer Science, Interdisciplinary Applications
Heqing Tan, Muqing Du, Anthony Chen
Summary: This paper proposes an accelerated algorithm for solving the non-additive traffic equilibrium problem by relaxing the additivity assumption in traditional models, achieving higher efficiency and robustness.
COMPUTERS & OPERATIONS RESEARCH
(2022)
Article
Management
Guoyuan Li, Anthony Chen
Summary: This paper proposes a strategy-based transit stochastic user equilibrium (SUE) model that considers capacity and number-of-transfers constraints in an urban congested transit network. The model uses a route-section-based method for network representation and assumes passengers' route choice behavior obeys the logit model. The transit line capacity and maximum number-of-transfers constraints are considered, and the problem is formulated as a variational inequality (VI) problem. A transit path-set generation procedure is proposed, and the asymmetric cost function is solved using the diagonalization method.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Economics
Muqing Du, Anthony Chen
Summary: Systematic uncertainty analysis is crucial for evaluating the variation in model outputs and identifying critical sources of uncertainty to enhance the reliability and stability of a system. This study presents a sensitivity-based uncertainty analysis approach in equilibrium transit systems, considering uncertainties caused by probabilistic travel demand, congestion, and vehicle frequencies. The proposed method incorporates the congestion effect in passengers' route-choice models and utilizes the hyperpath concept to handle the common-line problem at transit stops. The developed approach enables the simultaneous propagation of uncertainties from different input sources to the model outputs, contributing to the practical applications of sensitivity and uncertainty analyses.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2022)
Article
Engineering, Civil
Jiankun Zhou, Muqing Du, Anthony Chen
Summary: This paper proposes an improved network capacity model that takes into account the intermodal transportation in urban multimodal transportation systems. The model considers both mode split and traffic assignment, and uses mathematical methods to efficiently solve the complex problem. Numerical results demonstrate the advantages and features of the proposed model.
TRANSPORTATION RESEARCH RECORD
(2022)
Article
Transportation
Ruiya Chen, Xiangdong Xu, Anthony Chen, Xiaoning Zhang
Summary: This paper presents a conservative expected travel time approach, called MCET, for reporting reliable waiting time information in app-based transportation services, addressing the issues of existing information provision forms.
TRANSPORTMETRICA A-TRANSPORT SCIENCE
(2023)
Article
Transportation
Ruiya Chen, Xiangdong Xu, Anthony Chen, Chao Yang
Summary: Travel time variability poses challenges to reporting travel time information. This paper proposes a conservative expected travel time approach to enhance information reliability and simplicity.
TRANSPORTMETRICA B-TRANSPORT DYNAMICS
(2023)
Article
Environmental Studies
Yingying Xu, Ho-Yin Chan, Anthony Chen, Xintao Liu
Summary: This article evaluates and visualizes the accessibility and mobility of pedestrian networks around metro station areas in Hong Kong, highlighting significant differences and potential underlying causes.
ENVIRONMENT AND PLANNING B-URBAN ANALYTICS AND CITY SCIENCE
(2022)
Article
Economics
Yu Gu, Anthony Chen, Xiangdong Xu
Summary: This study proposes an optimization-based approach to rank the importance of link combinations and analyze network vulnerability in extreme and near-extreme cases of disruption. A vulnerability envelope concept is used, which considers the worst and best network performance under multiple-link disruptions. The results demonstrate that the consideration of near-extreme cases yields additional valuable information that is not generated by the traditional vulnerability analysis.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2023)
Article
Transportation Science & Technology
Yu Gu, Anthony Chen
Summary: This study proposes an advanced equilibrium mode choice model to analyze the mode choice behavior of emerging customized bus (CB) services. The model considers the unique characteristics of CB services, including seat reservation and loyalty scheme. The results demonstrate the importance of considering passenger loyalty and managing mode similarity and heterogeneity when modeling emerging CB services.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2023)
Article
Environmental Studies
Zhuowei Wang, Jiangbo Yu, Guoyuan Li, Chengxiang Zhuge, Anthony Chen
Summary: This study investigates the feasibility and policy implications of achieving carbon neutrality in Hong Kong's public transportation through a competitive bus-market mechanism. A dynamic bus-market evolution model is established using the system dynamics method, which incorporates a generalized Lotka-Volterra model and discrete choice model. The results suggest that relying on business-as-usual policies and market evolution may not be sufficient to achieve the desired level of zero-emission buses, and long-term subsidies for hydrogen buses and support for hydrogen stations are effective measures to promote the hydrogen bus market.
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
(2023)
Article
Geography
Ho-Yin Chan, Yingying Xu, Anthony Chen, Xintao Liu, Kason Ka Ching Cheung
Summary: This article introduces a proof-of-concept designer-in-the-loop schematic map drawing tool, which combines manual and automated approaches to provide technical interactivity between the user and the computer. Compared to existing methods, the proposed approach is more compatible with the framework of effective map design from psychological and aesthetic perspectives, and offers a range of options based on user preferences.
TRANSACTIONS IN GIS
(2023)
Article
Environmental Studies
Shiqi Wang, Yuze Li, Anthony Chen, Chengxiang Zhuge
Summary: This paper develops a data-driven micro-simulation optimization model for deploying charging infrastructure for a large-scale electric bus network. The model considers both traditional charging posts and wireless charging lanes. The results show that deploying both charging posts and WCLs leads to higher levels of service, energy savings, and reduced emissions compared to deploying only charging posts, although the total costs are slightly higher. Sensitivity analysis confirms that parameters associated with electric buses and charging facilities significantly influence the model outputs.
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
(2023)
Article
Economics
Zhandong Xu, Anthony Chen, Xiaobo Liu
Summary: This paper presents a continuous time surplus maximization bi-objective user equilibrium (C-TSmaxBUE) model, in which the users' variability toward the time and toll trade-off in a tolled road network is explicitly considered. The model assigns different users with different ratios of the time saved per unit of money (RTSMs), and infinite indifference curves are generated by considering continuously distributed RTSMs in the population. A path-based single-boundary adjustment (SBA) algorithm is developed to solve the problem, which adjusts RTSM boundaries and path flows simultaneously. Numerical results demonstrate the equilibrium flow pattern and the efficiency of the SBA algorithm in obtaining high-quality equilibrium solutions.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2023)
Article
Economics
Umer Mansoor, Arshad Jamal, Junbiao Su, N. N. Sze, Anthony Chen
Summary: Motorcycle crashes cause a significant number of fatalities and severe injuries worldwide, especially in developing countries. Machine learning methods have been found to provide better prediction performance, but with weaker interpretability. This study aims to compare the consistency of risk factors identified by statistical models and machine learning methods in analyzing motorcycle crash severity.
Article
Computer Science, Interdisciplinary Applications
Rafael Praxedes, Teobaldo Bulhoes, Anand Subramanian, Eduardo Uchoa
Summary: The Vehicle Routing Problem with Simultaneous Pickup and Delivery is a classical optimization problem that aims to determine the least-cost routes while meeting pickup and delivery demands and vehicle capacity constraints. In this study, a unified algorithm is proposed to solve multiple variants of the problem, and extensive computational experiments are conducted to evaluate the algorithm's performance.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Ragheb Rahmaniani, Teodor Gabriel Crainic, Michel Gendreau, Walter Rei
Summary: Benders decomposition (BD) is a popular solution algorithm for stochastic integer programs. However, existing parallelization methods often suffer from inefficiencies. This paper proposes an asynchronous parallel BD method and demonstrates its effectiveness through numerical studies and performance enhancement strategies.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Giulia Caselli, Maxence Delorme, Manuel Iori, Carlo Alberto Magni
Summary: This study addresses a real-world scheduling problem and proposes four exact methods to solve it. The methods are evaluated through computational experiments on different types of instances and show competitive advantages on specific subsets. The study also demonstrates the generalizability of the algorithms to related scheduling problems with contiguity constraints.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Shaowen Yao, Chao Tang, Hao Zhang, Songhuan Wu, Lijun Wei, Qiang Liu
Summary: This paper examines the problem of two-dimensional irregular multiple-size bin packing and proposes a solution that utilizes an iteratively doubling binary search algorithm to find the optimal bin combination, and further optimizes the result through an overlap minimization approach.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Decheng Wang, Ruiyou Zhang, Bin Qiu, Wenpeng Chen, Xiaolan Xie
Summary: Consideration of driver-related constraints, such as mandatory work break, in vehicle scheduling and routing is crucial for safety driving and protecting the interests of drivers. This paper addresses the drop-and-pull container drayage problem with flexible assignment of work break, proposing a mixed-integer programming model and an algorithm for solving realistic-sized instances. Experimental results show the effectiveness of the proposed algorithm in handling vehicle scheduling and routing with work break assignment.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
William N. Caballero, Jose Manuel Camacho, Tahir Ekin, Roi Naveiro
Summary: This research provides a novel probabilistic perspective on the manipulation of hidden Markov model inferences through corrupted data, highlighting the weaknesses of such models under adversarial activity and emphasizing the need for robustification techniques to ensure their security.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Davood Zaman Farsa, Shahryar Rahnamayan, Azam Asilian Bidgoli, H. R. Tizhoosh
Summary: This paper proposes a multi-objective evolutionary framework for compressing feature vectors using deep autoencoders. The framework achieves high classification accuracy and efficient image representation through a bi-level optimization scheme. Experimental results demonstrate the effectiveness and efficiency of the proposed framework in image processing tasks.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Matthew E. Scherer, Raymond R. Hill, Brian J. Lunday, Bruce A. Cox, Edward D. White
Summary: This paper discusses instance generation methods for the multidemand multidimensional knapsack problem and introduces a primal problem instance generator (PPIG) to address feasibility issues in current instance generation methods.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Yin Yuan, Shukai Li, Lixing Yang, Ziyou Gao
Summary: This paper investigates the design of real-time train regulation strategies for urban rail networks to reduce train deviations and passenger waiting times. A mixed-integer nonlinear programming (MINLP) model is used and an efficient iterative optimization (IO) approach is proposed to address the complexity. The generalized Benders decomposition (GBD) technique is also incorporated. Numerical experiments show the effectiveness and computational efficiency of the proposed method.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Xinghai Guo, Netirith Narthsirinth, Weidan Zhang, Yuzhen Hu
Summary: This study proposes a bi-level scheduling method that utilizes unmanned surface vehicles for container transportation. By formulating mission decision and path control models, efficient container transshipment and path planning are achieved. Experimental results demonstrate the effectiveness of the proposed approach in guiding unmanned surface vehicles to complete container transshipment tasks.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Review
Computer Science, Interdisciplinary Applications
Jose-Fernando Camacho-Vallejo, Carlos Corpus, Juan G. Villegas
Summary: This study aims to review the published papers on implementing metaheuristics for solving bilevel problems and performs a bibliometric analysis to track the evolution of this topic. The study provides a detailed description of the components of the proposed metaheuristics and analyzes the common combinations of these components. Additionally, the study provides a detailed classification of how crucial bilevel aspects of the problem are handled in the metaheuristics, along with a discussion of interesting findings.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Xudong Diao, Meng Qiu, Gangyan Xu
Summary: In this study, an optimization model for the design of an electric vehicle-based express service network is proposed, considering limited recharging resources and power management. The proposed method is validated through computational experiments on realistic instances.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Ramon Piedra-de-la-Cuadra, Francisco A. Ortega
Summary: This study proposes a procedure to select candidate sites optimally for ensuring energy autonomy and reinforced service coverage for electric vehicles, while considering demand and budget restrictions.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Danny Blom, Christopher Hojny, Bart Smeulders
Summary: This paper focuses on a robust variant of the kidney exchange program problem with recourse, and proposes a cutting plane method for solving the attacker-defender subproblem. The results show a significant improvement in running time compared to the state-of-the-art, and the method can solve previously unsolved instances. Additionally, a new practical policy for recourse is proposed and its tractability for small to mid-size kidney exchange programs is demonstrated.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Anqi Li, Congying Han, Tiande Guo, Bonan Li
Summary: This study proposes a general framework for designing linear programming instances based on the preset optimal solution, and validates the effectiveness of the framework through experiments.
COMPUTERS & OPERATIONS RESEARCH
(2024)
