Article
Environmental Sciences
Shuqin Zhao, Linzhong Liu, Ping Zhao
Summary: Traffic assignment in urban transport planning involves allocating traffic flows in a network. The traditional goal is to reduce travel time or costs, but environmental concerns have now become important. This study proposes a model based on cooperative game theory that incorporates vehicle emissions. The model includes a performance model to predict travel time and a cooperative game model to assign traffic flow based on emission reduction constraints.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Economics
Junyoung Kim, Byungju Goo, Youngjoo Roh, Chungmok Lee, Kyungsik Lee
Summary: The airport gate assignment problem aims to efficiently allocate gates to flights, taking into account unpredictable factors such as air traffic demands and weather conditions. A robust gate assignment plan is crucial for airport operators to handle flight schedule deviations effectively.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2023)
Article
Operations Research & Management Science
Qi Luo, Viswanath Nagarajan, Alexander Sundt, Yafeng Yin, John Vincent, Mehrdad Shahabi
Summary: This paper investigates the use of ride-pooling in mobility-on-demand (MoD) systems to enhance efficiency. Two approximation algorithms are proposed to solve the vehicle repositioning and ride-pooling assignment problem. The experiments show that these algorithms can parallelize computations and achieve optimal solutions with small gaps.
TRANSPORTATION SCIENCE
(2023)
Article
Robotics
Hyungjoon Yang, Je-Hun Lee, Sang Hyun Lee, Seung Gi Lee, Hyung Rok Kim, Hyun-Jung Kim
Summary: The task assignment and worker balancing problem in assembly lines is crucial for maximizing productivity. This study focuses on a real automotive parts assembly line where multiple workers perform various tasks simultaneously in a workstation, with each worker's processing time varying. New positional constraints are introduced to ensure each worker's working space. The goal is to minimize cycle time, and a filtered beam search algorithm is proposed to efficiently solve large-scale instances.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Management
Arne Schulz
Summary: This paper investigates the problem of maximally diverse grouping, describing optimal solutions for realistic input data and developing a new linear objective function for determining the best balanced solution. An integer program, detailed complexity analysis, and computational study are presented in the research.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Computer Science, Hardware & Architecture
Ibrahim Shaer, Greg Sidebottom, Anwar Haque, Abdallah Shami
Summary: The main goal of Egress Peer Engineering (EPE) is to optimize network resources, reduce costs, and avoid overloading by assigning and updating traffic flows in multiple steps. This study introduces an algorithm and two heuristics for generating execution plans based on the analysis of the problem.
Article
Mechanics
Changdong Zheng, Fangfang Xie, Tingwei Ji, Xinshuai Zhang, Yufeng Lu, Hongjie Zhou, Yao Zheng
Summary: This paper describes the introduction of expert demonstration into a classic off-policy RL algorithm, enabling rapid learning of active flow control strategies for vortex-induced vibration problems.
Article
Economics
Yu Jiang, Yasha Wang, Zhitao Hu, Qingwen Xue, Bin Yu
Summary: This paper proposes an airport gate assignment problem considering harbor safety constraints. A two-phase mathematical optimization model is constructed to optimize gate utilization efficiency while avoiding security conflicts. The improved branch-and-price method with label-based pricing algorithm and two acceleration strategies outperforms other solvers in terms of accuracy and efficiency.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2023)
Article
Automation & Control Systems
Mitsuru Toyoda, Mirai Tanaka
Summary: This study proposes an efficient algorithm for solving the sum-of-absolute-values (SOAV) minimization problem with linear equality and box constraints using the alternating direction method of multipliers (ADMM). The algorithm employs efficient methods for calculating proximal points to improve computation efficiency. The study proves the linear convergence of the proposed algorithm and demonstrates its advantages through a practical application.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2022)
Article
Computer Science, Interdisciplinary Applications
Mohammad Ali Habiballahi, Mohammad Tamannaei, Hossein Falsafain
Summary: This study addresses the Locomotive Assignment Problem (LAP) for freight trains and proposes solutions considering multiple factors. The experimental results show a mutual interaction between the LAP and the train formation problem.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Computer Science, Information Systems
Chaoqi Jia, Longkun Guo, Kewen Liao, Zhigang Lu
Summary: Constrained clustering with instance-level Must-Link (ML) and Cannot-Link (CL) auxiliary information has been extensively studied due to its broad applications. However, no algorithm has provided a non-trivial approximation ratio to the constrained k-means problem. To address this issue, we propose an algorithm with a provable approximation ratio of O(log k/) when only ML constraints are considered. Experimental results show that our algorithm outperforms existing greedy-based heuristic methods in clustering accuracy.
TSINGHUA SCIENCE AND TECHNOLOGY
(2023)
Article
Transportation Science & Technology
Tanapon Lilasathapornkit, David Rey, Wei Liu, Meead Saberi
Summary: This study introduces a new macroscopic user equilibrium traffic assignment problem framework for pedestrian networks, taking into account microscopic properties, and demonstrates its applicability in Sydney footpath networks.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2022)
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
Management
Maurizio Boccia, Adriano Masone, Claudio Sterle, Teresa Murino
Summary: Automated guided vehicles (AGVs) are widely used in AGV-based transportation systems for the movement of goods and materials. The scheduling of transfer jobs on AGVs is crucial to overcome delays in production and material handling processes. However, the issue of AGV battery depletion and recharge has been neglected in previous research. This study focuses on the AGV scheduling problem with battery constraints and proposes novel solution methods.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Radhwane Boufellouh, Faycal Belkaid
Summary: This paper investigates the energy-efficient flow shop scheduling problem with various constraints and proposes an enhanced multi-objective ant colony algorithm to solve this problem. Extensive experiments demonstrate the effectiveness of the proposed method and enhancements in obtaining high quality solutions, and showcase the significance of considering transportation speed control, battery management, and AGV idle power consumption.
APPLIED SOFT COMPUTING
(2023)
Article
Transportation
Zhandong Xu, Jun Xie, Xiaobo Liu, Yu (Marco) Nie
Summary: This paper proposes an assessment framework to quantify the competitiveness of transit compared to a taxi-like service. The framework uses a transit route builder to search for the best available transit route based on origin and destination of a given taxi trip. The competitiveness of transit is measured based on the traveler's preference and the generalized cost. The study finds that while most taxi trips are faster, only a small percentage of them are shorter. The relative competitiveness of transit increases with average trip distance and decreases with the passenger's value of time.
TRANSPORTMETRICA A-TRANSPORT SCIENCE
(2022)
Article
Operations Research & Management Science
Yanhong Wang, Rui Jiang, Yu (Marco) Nie, Ziyou Gao
Summary: Previous studies have shown that traffic oscillations can be induced by special network topology, and information about traffic conditions can affect these oscillations. By allowing a subset of drivers to be reactive, the system displays six new patterns depending on the ratio of reactive drivers, with only one stable solution fully utilizing road space between intersections. These findings highlight the link between information provision and topology-induced traffic oscillations, providing insights for designing strategies to mitigate their adverse impact.
TRANSPORTATION SCIENCE
(2021)
Article
Economics
Kenan Zhang, Yu (Marco) Nie
Summary: The study examines a transportation network company (TNC) offering on-demand solo and pooling e-hail services in a competitive market, establishing market equilibrium based on a driver-passenger matching model. Different pricing problems are analyzed, with a case study in Chicago showing that a mixed strategy of providing both solo and pooling rides achieves the highest profit and trip production in most scenarios. Minimum wage policies can improve social welfare in the short term but may be counterproductive in the long run, impacting the supply and demand of ride-hail services and exacerbating traffic congestion.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2021)
Article
Economics
Gongyuan Lu, Zili Shen, Xiaobo Liu, Yu (Marco) Nie, Zhiqiang Xiong
Summary: This study models and analyzes a futuristic intersection that serves connected, autonomous, and centrally managed vehicles. Three control strategies are examined to minimize system delay, with the first two abandoning signal timing and the third retaining it. The signal-free strategy shows greater efficiency, but relies on system safety and reliability. Introducing a fail-safe buffer degrades the efficiency but allows for signal-like behavior during congestion. Using signal timing in managing the intersection brings computational benefits by eliminating conflicts. The basic logic of signal timing may still be relevant even when humans are not driving.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2022)
Article
Operations Research & Management Science
Zhandong Xu, Jun Xie, Xiaobo Liu, Yu (Marco) Nie
Summary: This paper proposes a modeling framework for strategy-based equilibrium traffic assignment (SETA) problems and obtains more precise solutions at a lower computational cost using the hyperbush algorithm (HBA). Experimental results demonstrate the superior efficiency and solution quality of the HBA algorithm.
TRANSPORTATION SCIENCE
(2022)
Article
Operations Research & Management Science
Ruijie Li, Yu (Marco) Nie, Xiaobo Liu
Summary: This paper proposes a quantity-based demand management system that promotes ridesharing through auctioning permits and encouraging commuters to share. Results of a numerical experiment show that this system effectively promotes ridesharing, benefiting all stakeholders.
TRANSPORTATION SCIENCE
(2022)
Article
Economics
Kenan Zhang, Yu (Marco) Nie
Summary: This paper analyzes and evaluates several policies to mitigate the congestion effect caused by a Transportation Network Company (TNC) in an idealized city. The study finds that a trip-based policy delivers the best performance in reducing congestion and improving social welfare, based on a case study of Chicago.
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
(2022)
Article
Economics
Gongyuan Lu, Jia Ning, Xiaobo Liu, Yu (Marco) Nie
Summary: This paper proposes a route-based model for the Train Platforming and Rescheduling Problem (TPRP) that can accommodate various interlocking mechanisms and reduce the size of optimization problems. Several case studies validate the effectiveness of the proposed model in producing high-quality platform/schedule decisions and the heuristic algorithms in providing high-quality approximate solutions at a lower computational cost.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2022)
Article
Economics
Hongyuan Yang, Yu (Marco) Nie
Summary: This study analyzes the risks involved in riding various transit modes during and after a global pandemic, investigates factors affecting the risk, and formulates models for transit operator's design problems. It finds that optimizing vehicle capacity and staff testing frequency, as well as considering passenger behavior and different levels of infection prevalence, are crucial in mitigating risk and efficiently managing service during a pandemic.
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
(2022)
Article
Economics
Enhui Chen, Amanda Stathopoulos, Yu (Marco) Nie
Summary: This study uses a large-scale transit smart card dataset to analyze transfer station choices in bus-rail intermodal trips. The results show that the nearest-station heuristics often don't apply, and commuters' transfer station selections are influenced by trip attributes of all involved modes. The study also reveals the factors that define station catchment areas, such as location attributes and amenities.
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
(2022)
Article
Economics
Tianxing Dai, Jiayang Li, Yu (Marco) Nie
Summary: This study proposes a new strategic transit design methodology that prioritizes accessibility and equity. By using ethical principles, the study aims to enhance vertical equity. The difference principle is identified as the representative principle among the four ethical principles considered. The study develops a corridor transit design model that accounts for spatial supply heterogeneity. The results show that the egalitarian design improves equity, while the utilitarian design exacerbates inequity, especially when there is uneven spatial distribution of opportunities. The difference principle is useful in identifying the upper limit of equity within resource constraints or problem structures.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2023)
Book Review
Economics
Yu (Marco) Nie, Vaclav Smil
PAPERS IN REGIONAL SCIENCE
(2023)
Article
Operations Research & Management Science
Zhandong Xu, Jun Xie, Xiaobo Liu, Yu (Marco) Nie
Summary: This paper introduces the strategy-based equilibrium traffic assignment (SETA) problem and proposes a hypergraph algorithm (HBA) to solve it. By decomposing the hypergraph into hypergraph clusters and limiting traffic assignments within these clusters, HBA obtains more precise solutions in less time and with fewer computational resources.
TRANSPORTATION SCIENCE
(2022)
Article
Multidisciplinary Sciences
Xiaobo Liu, Gongyuan Lu, Fangfang Zheng, Ruijie Li, Peng Cao, You Kong, Yu (Marco) Nie
CHINESE SCIENCE BULLETIN-CHINESE
(2020)