Shiwei He

Innovative Bike-Sharing in China: Solving Faulty Bike-Sharing Recycling Problem

In China, based on the mobile Internet technology and global positioning system (GPS), innovative bike-sharing is different from traditional bike-sharing system with docking station, for its flexibility and convenience. However, innovative bike-sharing system faces operational challenges, especially in faulty bike-sharing recycling (FBSR) problem. In this paper, a framework is designed based on the optimization method to solve the FBSR problem so that it can minimize the total recycling costs by taking the route optimization and loading capacity ratio as constraints. The FBSR method combines the K-means method for clustering faulty bike-sharing with planning recycling route for operational decisions. Moreover, CPLEX solver is used to obtain the desired result of the FBSR model. Finally, a case study based on a certain area in Beijing, China, is used to verify the validity and applicability of the model. The results show that the value of loading capacity ratio and the number of clustering points greatly affect the results of FBSR problem. Four vehicles are designated to execute FBSR tasks required by different clustering points. This study is of considerable significance for the bike-sharing promotion in the last-mile situation to the real problems arising in the initial period.

Dynamic railcar connection planning in classification yards

This paper investigates dynamic railcar planning in railroad classification yards. The plan decides the assignment of railcars from inbound trains to outbound trains under various size limitations of outbound trains and allows dynamic sequencing of inbound train classification and outbound train assembly. A mixed-integer program is presented for the problem along with a heuristic algorithm based on the harmony search strategy. The numerical results based on both a real-world case and randomly created instances show that dynamic sequencing can reduce total dwell time compared to static sequencing, especially when more trains are classified at a yard. However, the savings on average dwell time for each railcar become smaller when the traffic volume goes up. Once the volume through a yard is close to its capacity, the dwell time per rail car goes up very quickly and the benefit of dynamic sequencing diminishes. It implies that the benefit of dynamic sequencing is more significant for yards with lower traffic volume.

Synthetic Optimization Model and Algorithm for Railway Freight Center Station Location and Wagon Flow Organization Problem

The railway freight center stations location and wagon flow organization in railway transport are interconnected, and each of them is complicated in a large-scale rail network. In this paper, a two-stage method is proposed to optimize railway freight center stations location and wagon flow organization together. The location model is present with the objective to minimize the operation cost and fixed construction cost. Then, the second model of wagon flow organization is proposed to decide the optimal train service between different freight center stations. The location of the stations is the output of the first model. A heuristic algorithm that combined tabu search (TS) with adaptive clonal selection algorithm (ACSA) is proposed to solve those two models. The numerical results show the proposed solution method is effective.

The aggravation of urban air quality deterioration due to urbanization, transportation and economic development – Panel models with marginal effect analyses across China

In this paper, panel data models are established to examine the impacts of urban construction, transport facilities, and economic development on the urban air quality. Combined with data from different tiers of Chinese cities for two time series, 2010 and 2015, the variable-intercept model (VIM) is used to determine the parameters and significance of each independent variable. The marginal effects of different categories of independent variables (urbanization, transportation and economy) on the urban air quality are also studied with regard to the results of different VIMs. The results show that transportation factors (such as annual passenger trips, bus numbers and taxi numbers) have the most significant effects on the air quality for all the Chinese cities. Moreover, urbanized area and annual gross value of industrial output also have prominent impacts on the air quality across China. In addition, the marginal effects of the air quality index obtained via VIMs with classified local variables reflect that the influences of urbanization, transportation and economy on urban air quality are substantially different among different tiers of cities. Therefore, based on the findings, we propose measures to improve air quality for different tiers of cities, such as rational use of space resources, optimizing transport modes, and encouraging carpooling.

Methodology of mixed load customized bus lines and adjustment based on time windows

Custom bus routes need to be optimized to meet the needs of a customized bus for personalized trips of different passengers. This paper introduced a customized bus routing problem in which trips for each depot are given, and each bus stop has a fixed time window within which trips should be completed. Treating a trip as a virtual stop was the first consideration in solving the school bus routing problem (SBRP). Then, the mixed load custom bus routing model was established with a time window that satisfies its requirement and the result were solved by Cplex software. Finally, a simple network diagram with three depots, four pickup stops, and five delivery stops was structured to verify the correctness of the model, and based on the actual example, the result is that all the buses ran 124.42 kilometers, the sum of kilometers was 10.35 kilometers less than before. The paths and departure times of the different busses that were provided by the model were evaluated to meet the needs of the given conditions, thus providing valuable information for actual work.

A Simulation Platform for Combined Rail/Road Transport in Multiyards Intermodal Terminals

With the rapid development of multiyards railway intermodal terminal (MYRIT) construction in China, performance evaluation has become an important issue for terminal design and management departments. Due to the complexity of the multiyards terminal and the associated rail network, the train moving process and related terminal operations have become more complicated compared with the traditional intermodal container terminal. However, in general simulation platforms, the train moving process is simplified and train route scheduling rules are not considered in existing simulation models. In order to provide an accurate and comprehensive quantitative evaluation tool for MYRIT, a simulation platform based on the Timed Petri Net model has been developed, which can offer decision support for terminal design and management departments. In this platform, a yards and facilities layout module has been created to give simulation users access to designing the railway network on this platform. And a train route dispatching simulation method has been integrated to provide an accurate simulation of the train moving process. Based on a real case of Qianchang railway intermodal terminal that is located in Fujian Province, China, the platform is thoroughly validated against historical data. And the test scenarios show that train routes arrangement and handling equipment configuration both have a significant influence on overall terminal performance, which need to be carefully considered during terminal design and management.

Optimization of Classification Track Assignment Considering Block Sequence at Train Marshaling Yard

An operational process at train marshaling yard is considered in this study. The inbound trains are decoupled and disassembled into individual railcars, which are then moved to a series of classification tracks, forming outbound trains after being assembled and coupled. We focus on the allocation plan of the classification tracks. Given are the disassembling and assembling sequence, the railcars connection plan, and a number of classification tracks. Output is the assignment of the railcars to the classification tracks. An integer programming model is proposed, aimed at reducing the number of coupling operations, as well as the number of dirty tracks which is related to the rehumping operation, and the order of the railcars on the outbound train must satisfy the block sequence. Tabu algorithm is designed to solve the problem, and the model is also tested by CPLEX in comparison. A numerical experiment based on a real-world case is analyzed, and the result can be reached within a reasonable amount of time. We also discussed a number of factors that may affect the track assignment and gave suggestions for the real-world case.

Multiperiod Hierarchical Location Problem of Transit Hub in Urban Agglomeration Area

With the rapid urbanization in developing countries, urban agglomeration area (UAA) forms. Also, transportation demand in UAA grows rapidly and presents hierarchical feature. Therefore, it is imperative to develop models for transit hubs to guide the development of UAA and better meet the time-varying and hierarchical transportation demand. In this paper, the multiperiod hierarchical location problem of transit hub in urban agglomeration area (THUAA) is studied. A hierarchical service network of THUAA with a multiflow, nested, and noncoherent structure is described. Then a multiperiod hierarchical mathematical programming model is proposed, aiming at minimizing the total demand weighted travel time. Moreover, an improved adaptive clonal selection algorithm is presented to solve the model. Both the model and algorithm are verified by the application to a real-life problem of Beijing-Tianjin-Hebei Region in China. The results of different scenarios in the case show that urban population migration has a great impact on the THUAA location scheme. Sustained and appropriate urban population migration helps to reduce travel time for urban residents.

Multiobjective Optimization Method of Public Transit Networks Based on Travel Behavior

AbstractThe optimization of transit network can improve transit efficiency and traffic conditions as well as reduce environmental pollution. Transit network optimization that considers the travel behavior of bus passengers comprises four steps. First, a bypass strategy is employed to optimize the bus lines according to the situation of urban traffic congestion. Second, direct ratio is calculated to determine the optimal network. Third, minimum transfer is sought by using the space P method to construct and analyze a transit network model. In building a network adjacency matrix, the Floyd algorithm is used to obtain the matrix of minimum transfers between two stops. The Breadth-First Search algorithm is used to search the bus routes with the shortest transfer time. Fourth, all the bus lines of the same origin-destination are optimized to obtain the shortest travel time. Numerical experiments show that the proposed method can reasonably and efficiently achieve network optimization within a given area.

Robust optimization model and algorithm for railway freight center location problem in uncertain environment

Railway freight center location problem is an important issue in railway freight transport programming. This paper focuses on the railway freight center location problem in uncertain environment. Seeing that the expected value model ignores the negative influence of disadvantageous scenarios, a robust optimization model was proposed. The robust optimization model takes expected cost and deviation value of the scenarios as the objective. A cloud adaptive clonal selection algorithm (C-ACSA) was presented. It combines adaptive clonal selection algorithm with Cloud Model which can improve the convergence rate. Design of the code and progress of the algorithm were proposed. Result of the example demonstrates the model and algorithm are effective. Compared with the expected value cases, the amount of disadvantageous scenarios in robust model reduces from 163 to 21, which prove the result of robust model is more reliable.