scholarly journals An Optimization Model for Demand-Responsive Feeder Transit Services Based on Ride-Sharing Car

Information ◽  
2019 ◽  
Vol 10 (12) ◽  
pp. 370 ◽  
Author(s):  
Bo Sun ◽  
Ming Wei ◽  
Wei Wu
Keyword(s):  
Time Windows ◽  
Model Performance ◽  
Optimal Solution ◽  
Walking Distance ◽  
Ride Sharing ◽  
Chongqing City ◽  
Feeder Transit ◽  
Transit Services ◽  
Integrated Operation ◽  
The Difference

Ride-sharing (RS) plays an important role in saving energy and alleviating traffic pressure. The vehicles in the demand-responsive feeder transit services (DRT) are generally not ride-sharing cars. Therefore, we proposed an optimal DRT model based on the ride-sharing car, which aimed at assigning a set of vehicles, starting at origin locations and ending at destination locations with their service time windows, to transport passengers of all demand points to the transportation hub (i.e., railway, metro, airport, etc.). The proposed model offered an integrated operation of pedestrian guidance (from unvisited demand points to visited ones) and transit routing (from visited ones to the transportation hub). The objective was to simultaneously minimize weighted passenger walking and riding time. A two-stage heuristic algorithm based on a genetic algorithm (GA) was adopted to solve the problem. The methodology was tested with a case study in Chongqing City, China. The results showed that the model could select optimal pick-up locations and also determine the best pedestrian and route plan. Validation and analysis were also carried out to assess the effect of maximum walking distance and the number of share cars on the model performance, and the difference in quality between the heuristic and optimal solution was also compared.

scholarly journals A Green Demand-Responsive Airport Shuttle Service Problem with Time-Varying Speeds

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Ming Wei ◽  
Binbin Jing ◽  
Jian Yin ◽  
Yang Zang
Keyword(s):  
Time Windows ◽  
Operating Cost ◽  
Model Performance ◽  
Path Selection ◽  
Mixed Integer ◽  
Time Varying ◽  
Alternative Fuel Vehicles ◽  
Nsga Ii ◽  
The Difference ◽  
On The Road

This study proposes a multiobjective mixed integer linear programming (MOMILP) model for a demand-responsive airport shuttle service. The approach aims to assign a set of alternative fuel vehicles (AFVs) located at different depots to visit each demand point within the specified time and transport all of them to the airport. The proposed model effectively captures the interactions between path selection and environmental protection. Moreover, users with flexible pick-up time windows, the time-varying speed of vehicles on the road network, and the limited fuel for the route duration are also fully considered in this model. The work aims at simultaneously minimizing the operating cost, vehicle fuel consumption, and CO2 emissions. Since this task is an NP-hard problem, a heuristic-based nondominated sorting genetic algorithm (NSGA-II) is also presented to find Pareto optimal solutions in a reasonable amount of time. Finally, a real-world example is provided to illustrate the proposed methodology. The results demonstrate that the model not only selects an optimal depot for each AFV but also determines its route and timetable plan. A sensitivity analysis is also given to assess the effect of early/late arrival penalty weights and the number of AFVs on the model performance, and the difference in quality between the proposed and traditional models is compared.

scholarly journals Optimal Integrated Model for Feeder Transit Route Design and Frequency-Setting Problem with Stop Selection

2020 ◽  
Vol 2020 ◽  
pp. 1-12 ◽  
Author(s):  
Ming Wei ◽  
Tao Liu ◽  
Bo Sun ◽  
Binbin Jing
Keyword(s):  
Walking Distance ◽  
Load Factor ◽  
Chongqing City ◽  
Proposed Model ◽  
Route Design ◽  
Feeder Transit ◽  
Total Travel Time ◽  
Test Instance ◽  
Np Hard Problem ◽  
Lower Limits

This study proposed a mathematical model for designing a feeder transit service for improving the service quality and accessibility of transportation hubs (such as airport and rail station). The proposed model featured an integrated framework, which simultaneously guided passengers to reach their nearest stops to get on and off the bus, designed routes to transport passengers from these selected pick-up stops to the transportation hubs, and calculated their departure frequencies. In particular, the maximum walking distance, the upper and lower limits of route frequencies, and the load factor rate of each route were fully accounted for in this study. The main objective of the proposed model was to simultaneously minimize the total walking, riding time, and waiting time of all passengers. As this study explored an NP-hard problem, a two-stage genetic algorithm combining the Dijkstra search method was further developed to yield metaoptimal solutions to the model within an acceptable time. Finally, a test instance in Chongqing City, China, demonstrated that the proposed model was an effective tool to generate a pedestrian, route, and operation plan; it reduced the total travel time, compared with the traditional model.

Fuzzy-neural-network-based fluctuation smoothing rule for reducing the cycle times of jobs with various priorities in a wafer fabrication plant: A simulation study

2009 ◽  
Vol 223 (8) ◽  
pp. 1033-1043 ◽  
Author(s):  
T Chen
Keyword(s):  
Neural Network ◽  
Cycle Time ◽  
Fuzzy Neural Network ◽  
Optimal Solution ◽  
Wafer Fabrication ◽  
Estimation Accuracy ◽  
Cycle Times ◽  
Fuzzy Neural ◽  
The Difference ◽  
Fluctuation Smoothing

This paper presents a fuzzy-neural-network-based fluctuation smoothing rule to further improve the performance of scheduling jobs with various priorities in a wafer fabrication plant. The fuzzy system is modified from the well-known fluctuation smoothing policy for a mean cycle time (FSMCT) rule with three innovative treatments. First, the remaining cycle time of a job is estimated by applying an existing fuzzy-neural-network-based approach to improve the estimation accuracy. Second, the components of the FSMCT rule are normalized to balance their importance. Finally, the division operator is applied instead of the traditional subtraction operator in order to magnify the difference in the slack and to enhance the responsiveness of the FSMCT rule. To evaluate the effectiveness of the proposed methodology, production simulation is applied to generate some test data. According to the experimental results, the proposed methodology outperforms six existing approaches in the reduction of the average cycle times. In addition, the new rule is shown to be a Pareto optimal solution for scheduling jobs in a semiconductor manufacturing plant.

scholarly journals An alternative way to evaluate chemistry-transport model variability

2017 ◽  
Vol 10 (3) ◽  
pp. 1199-1208 ◽  
Author(s):  
Laurent Menut ◽  
Sylvain Mailler ◽  
Bertrand Bessagnet ◽  
Guillaume Siour ◽  
Augustin Colette ◽  
...  
Keyword(s):  
Transport Model ◽  
Model Performance ◽  
Error Statistics ◽  
Chemistry Transport Model ◽  
Temporal Correlations ◽  
Time Period ◽  
The Difference ◽  
Model Variability ◽  
Spatial Locations ◽  
Statistical Indicators

Abstract. A simple and complementary model evaluation technique for regional chemistry transport is discussed. The methodology is based on the concept that we can learn about model performance by comparing the simulation results with observational data available for time periods other than the period originally targeted. First, the statistical indicators selected in this study (spatial and temporal correlations) are computed for a given time period, using colocated observation and simulation data in time and space. Second, the same indicators are used to calculate scores for several other years while conserving the spatial locations and Julian days of the year. The difference between the results provides useful insights on the model capability to reproduce the observed day-to-day and spatial variability. In order to synthesize the large amount of results, a new indicator is proposed, designed to compare several error statistics between all the years of validation and to quantify whether the period and area being studied were well captured by the model for the correct reasons.

scholarly journals Location Routing Problem with Consideration of CO2 Emissions Cost: A Case Study

2020 ◽  
Vol 21 (2) ◽  
pp. 225-234
Author(s):  
Ananda Noor Sholichah ◽  
Y Yuniaristanto ◽  
I Wayan Suletra
Keyword(s):  
Co2 Emissions ◽  
Time Windows ◽  
Optimal Solution ◽  
Mixed Integer ◽  
Distribution Centers ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Location Routing ◽  
Study Results

Location and routing are the main critical problems investigated in a logistic. Location-Routing Problem (LRP) involves determining the location of facilities and vehicle routes to supply customer's demands. Determination of depots as distribution centers is one of the problems in LRP.  In LRP, carbon emissions need to be considered because these problems cause global warming and climate change. In this paper, a new mathematical model for LRP considering CO2 emissions minimization is proposed. This study developed a new  Mixed Integer Linear Programming (MILP)  model for LRP with time windows and considered the environmental impacts.  Finally, a case study was conducted in the province of Central Java, Indonesia. In this case study, there are three depot candidates. The study results indicated that using this method in existing conditions and constraints provides a more optimal solution than the company's actual route. A sensitivity analysis was also carried out in this case study.

scholarly journals Distilling Deep Structural Facial Relationships for FAU Intensity Estimation

2021 ◽  
Author(s):  
Yingruo Fan ◽  
Jacqueline CK Lam ◽  
Victor On Kwok Li
Keyword(s):  
Structural Characteristics ◽  
Model Performance ◽  
Training Model ◽  
Model Parameters ◽  
Intensity Estimation ◽  
Structural Relationships ◽  
Proposed Model ◽  
Comparable Performance ◽  
Knowledge Distillation ◽  
The Difference

<div> <div> <div> <p>Facial emotions are expressed through a combination of facial muscle movements, namely, the Facial Action Units (FAUs). FAU intensity estimation aims to estimate the intensity of a set of structurally dependent FAUs. Contrary to the existing works that focus on improving FAU intensity estimation, this study investigates how knowledge distillation (KD) incorporated into a training model can improve FAU intensity estimation efficiency while achieving the same level of performance. Given the intrinsic structural characteristics of FAU, it is desirable to distill deep structural relationships, namely, DSR-FAU, using heatmap regression. Our methodology is as follows: First, a feature map-level distillation loss was applied to ensure that the student network and the teacher network share similar feature distributions. Second, the region-wise and channel-wise relationship distillation loss functions were introduced to penalize the difference in structural relationships. Specifically, the region-wise relationship can be represented by the structural correlations across the facial features, whereas the channel-wise relationship is represented by the implicit FAU co-occurrence dependencies. Third, we compared the model performance of DSR-FAU with the state-of-the-art models, based on two benchmarking datasets. Our proposed model achieves comparable performance with other baseline models, though requiring a lower number of model parameters and lower computation complexities. </p> </div> </div> </div>

scholarly journals Research on Planning and Model Design of Micro-cycle Bus Line Based on Metro Station Connection

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Qiushui Fang ◽  
Zhingming Li ◽  
Zhen Wang ◽  
Jincheng Wu ◽  
Hongling Yu ◽  
...  
Keyword(s):  
Public Transport ◽  
Public Transportation ◽  
Travel Demand ◽  
Urban Expansion ◽  
Optimal Solution ◽  
Walking Distance ◽  
Model Design ◽  
Metro Station ◽  
City Bus ◽  
The Cost

Public transport coverage fails to keep pace with urbanization and urban expansion, which makes the “last kilometer" problem of residents’ travel increasingly prominent”. However, the practice has proved that microcirculation public transportation plays an important role in expanding the coverage of public transportation and promoting the integration of public transportation. Therefore, this paper takes a city bus community as an example. Firstly, it analyses the bus travel demand of commuters connecting to the subway station during the early workday rush hours on basis of IC Big Data, obtains candidate stations of microcirculation bus lines through K-means clustering. Secondly, it establishes the model, the target of which is to minimize  the cost residents' travel and bus operation, under the limited condition of walking distance, passenger number, station spacing and departure frequency. Finally, the genetic algorithm is used to find the optimal solution of the model, so it’s no doubt that the most feasible circular bus route is obtained. The results have positive significance for promoting the construction and operation of public transport integration and promoting the convenience and efficiency of public transport travel. 

scholarly journals Surface melt and the importance of water flow – an analysis based on high-resolution unmanned aerial vehicle (UAV) data for an Arctic glacier

2020 ◽  
Vol 14 (2) ◽  
pp. 549-563 ◽  
Author(s):  
Eleanor A. Bash ◽  
Brian J. Moorman
Keyword(s):  
Water Flow ◽  
Model Performance ◽  
Model Error ◽  
Two Dimensions ◽  
Glacier Mass Balance ◽  
Glacier Surface ◽  
Technological Advances ◽  
Flow Features ◽  
Surface Melt ◽  
The Difference

Abstract. Models of glacier surface melt are commonly used in studies of glacier mass balance and runoff; however, with limited data available, most models are validated based on ablation stakes and data from automatic weather stations (AWSs). The technological advances of unmanned aerial vehicles (UAVs) and structure from motion (SfM) have made it possible to measure glacier surface melt in detail over larger portions of a glacier. In this study, we use melt measured using SfM processing of UAV imagery to assess the performance of an energy balance (EB) and enhanced temperature index (ETI) melt model in two dimensions. Imagery collected over a portion of the ablation zone of Fountain Glacier, Nunavut, on 21, 23, and 24 July 2016 was previously used to determine distributed surface melt. An AWS on the glacier provides some measured inputs for both models as well as an additional check on model performance. Modelled incoming solar radiation and albedo derived from UAV imagery are also used as inputs for both models, which were used to estimate melt from 21 to 24 July 2016. Both models estimate total melt at the AWS within 16 % of observations (4 % for ETI). Across the study area the median model error, calculated as the difference between modelled and measured melt (EB = −0.064 m, ETI = −0.050 m), is within the uncertainty of the measurements. The errors in both models were strongly correlated to the density of water flow features on the glacier surface. The relation between water flow and model error suggests that energy from surface water flow contributes significantly to surface melt on Fountain Glacier. Deep surface streams with highly asymmetrical banks are observed on Fountain Glacier, but the processes leading to their formation are missing in the model assessed here. The failure of the model to capture flow-induced melt would lead to significant underestimation of surface melt should the model be used to project future change.

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