A static bike repositioning model in a hub-and-spoke network framework

Huang, Di; Chen, Xinyuan; Liu, Zhiyuan; Lyu, Cheng; Wang, Shuaian; Chen, Xuewu

doi:10.1016/j.tre.2020.102031

Cited by 53 publications

(18 citation statements)

References 69 publications

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“…To average out the effects of randomness in the request generation, 1000 replications of a single-trip operation were run to provide statistical estimates of the system performance for each kind of dynamic event. e offline routing model was solved by GRUOBI (version 9.0) through the YALMIP platform to achieve the optimal results [27].…”

Section: Simulation Resultsmentioning

confidence: 99%

Vehicle Routing and Scheduling of Flex-Route Transit under a Dynamic Operating Environment

Zheng

Gao

2021

Discrete Dynamics in Nature and Society

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To improve the reliability, responsiveness, and productivity of the flex-route transit service, this paper investigates the vehicle scheduling and routing problem under a dynamic operating environment. First, we discuss the new operating polices after the introduction of intelligent transportation systems (ITSs), including automatic vehicle location (AVL) system, mobile data terminal (MDT), and computer-aided dispatch (CAD) system. Second, a mixed integer programming (MIP) formulation is employed to solve the offline routing problem. Third, an online scheduling scheme is presented to tackle different dynamic events, such as dynamic requests, travel time fluctuations, cancellations of requests, and customer no-shows. Finally, simulation experiments based on a real-life flex-route transit service are conducted to assess the influence of different dynamic events. The results demonstrate that the proposed scheduling scheme is reliable for coping with various dynamic events, and our findings can be used to guide the policy making of flex-route transit services.

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Section: Simulation Resultsmentioning

confidence: 99%

Vehicle Routing and Scheduling of Flex-Route Transit under a Dynamic Operating Environment

Zheng

Gao

2021

Discrete Dynamics in Nature and Society

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“…Stochastic programming is one of the emerging methods to deal with uncertain problems. e stochastic programming method was developed by Danzig and Beare, aiming to model random variables by using a set of discrete scenarios with known probabilities [14][15][16][17]. e demand assumption in stochastic planning is a random variable that obeys a uniform distribution, a normal distribution, or a Poisson distribution.…”

Section: Mathematical Modelling Methods For Uncertain Problemsmentioning

confidence: 99%

“…In the reconstructing model, the first and second formulas of objective function (15) represent the total fixed cost and the expected acquisition cost, respectively. e first and second formulas in ( 16) represent carbon emissions during construction and collection, respectively.…”

Section: Reconstruction Of Stochastic Programming Model Of Wco For Biodiesel Supply Chain Under Supply Disturbancementioning

confidence: 99%

Stochastic Programming of Sustainable Waste Cooking Oil for Biodiesel Supply Chain under Uncertainty

Geng

Sun

2021

Journal of Advanced Transportation

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As an important emission reduction source for the transportation industry, biofuel has received strong support from the Chinese government. However, the development of the biofuel industry is still struggling. The high degree of uncertainty makes the development of the industry face huge challenges. Kitchen waste, as a biodiesel raw material with a large yield, has good development prospects. Reuse of kitchen waste can solve public health and safety problems. This paper proposes a two-stage stochastic programming model under supply disturbance to optimize the supply chain from the perspective of contract. Then current three main flow directions of kitchen waste are analysed and the reasonable price for biodiesel operators to purchase is determined. By signing contracts with the biodiesel operators, restaurant is guaranteed and encouraged to provide a certain percentage of kitchen waste to meet the demand for biodiesel production. Using actual case in the Yangtze River Delta region, the performance of the stochastic programming model under disturbance was compared. Through the sensitivity analysis of different parameters, this paper determines the influence of its supply chain network design and expected total system cost. Through the optimization of the waste cooking oil (WCO) for biodiesel supply chain, this paper can effectively improve the efficiency of the supply chain, reduce system costs, increase the profits of biofuel operators, and promote the sustainable development of the biofuel industry.

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“…It is the principle of the combined prediction model. e IOWA operator can give weight according to the prediction accuracy of each prediction model at each time and establish a combined prediction model with the sum of square error as the objective function [28][29][30]. IOWA operator theory is introduced as follows [31].…”

Section: Combined Prediction Model Of Civil Aviationmentioning

confidence: 99%

Forecasting Civil Aviation Incident Rate in China Using a Combined Prediction Model

Sun

Geng

2021

Journal of Advanced Transportation

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With the rapid development of air transportation, the complexity, importance, and severity of civil aviation safety have gradually become prominent. It is essential to use various data to analyze and predict the level of aviation safety. This paper used a combined prediction model based on Induced Ordered Weighted Averaging (IOWA) operator to forecast the civil aviation incident rate. We compiled and calculated civil aviation incident data and total flight hours from 2008 to 2019 in China and took the civil aviation incident rate (incident numbers per ten thousand flight hours) as the prediction object. First, this paper used the nonlinear regression model, Grey Verhulst model, and Holt-Winters exponential smoothing model to forecast the civil aviation incident rate individually. Then, it used the smallest sum of squared errors as the principle to use a combined prediction model based on the IOWA operator. It can be seen from the experimental results that the prediction accuracy of the combined model is better than single models. Finally, this paper forecasted the civil aviation incident rate in 2020 and 2021. The results showed that the predicted rates are 0.524 and 0.551. Most notably the incident rate will increase significantly compared with 2019.

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A static bike repositioning model in a hub-and-spoke network framework

Cited by 53 publications

References 69 publications

Vehicle Routing and Scheduling of Flex-Route Transit under a Dynamic Operating Environment

Vehicle Routing and Scheduling of Flex-Route Transit under a Dynamic Operating Environment

Stochastic Programming of Sustainable Waste Cooking Oil for Biodiesel Supply Chain under Uncertainty

Forecasting Civil Aviation Incident Rate in China Using a Combined Prediction Model

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