scholarly journals A Queuing Network Based Optimization Model for Calculating Capacity of Subway Station

2017 ◽  
Vol 2017 ◽  
pp. 1-7
Author(s):  
Hanchuan Pan ◽  
Zhigang Liu
Keyword(s):  
Optimization Model ◽  
Subway Station ◽  
Queuing Model ◽  
Selection Probability ◽  
Evaluation Indexes ◽  
State Dependent ◽  
Decision Variables ◽  
Proposed Model ◽  
Shanghai Metro

Capacity of subway station is an important factor to ensure the safety and improve the transportation efficiency. In this paper, based on the M/G/C/C state-dependent queuing model, a probabilistic selection optimization model is proposed to assess the capacity of the station. The goal of the model is to maximize the output rate of the station, and the decision variables of the model are the selection results of the passengers. Finally, this paper takes a subway station of Shanghai Metro as a case study and calculates the optimal selection probability. The proposed model could be used to analyze the average waiting time, congestion probability, and other evaluation indexes; at the same time, it verifies the validity and practicability of the model.

scholarly journals A Cost Optimization Model for Multiresource Leveling Problem without Project Duration Constraint

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Qingyou Yan ◽  
Qian Zhang ◽  
Xin Zou
Keyword(s):  
Optimization Model ◽  
Cost Optimization ◽  
Resource Usage ◽  
Project Duration ◽  
Resource Demand ◽  
Resource Leveling ◽  
Proposed Model ◽  
Liquidated Damages ◽  
The Relationship

The study of traditional resource leveling problem aims at minimizing the resource usage fluctuations and obtaining sustainable resource supplement, which is accomplished by adjusting noncritical activities within their start and finish time. However, there exist limitations in terms of the traditional resource leveling problem based on the fixed project duration. This paper assumes that the duration can be changed in a certain range and then analyzes the relationship between the scarce resource usage fluctuations and project cost. This paper proposes an optimization model for the multiresource leveling problem. We take into consideration five kinds of cost: the extra hire cost when the resource demand is greater than the resource available amount, the idle cost of resource when the resource available amount is greater than the resource demand, the indirect cost related to the duration, the liquidated damages when the project duration is extended, and the incentive fee when the project duration is reduced. The optimal objective of this model is to minimize the sum of the aforementioned five kinds of cost. Finally, a case study is examined to highlight the characteristic of the proposed model at the end of this paper.

scholarly journals Impact of Prioritization on the Outpatient Queuing System in the Emergency Department with Limited Medical Resources

Symmetry ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 796 ◽  
Author(s):  
Ao Zhang ◽  
Xiaomin Zhu ◽  
Qian Lu ◽  
Runtong Zhang
Keyword(s):  
Emergency Department ◽  
Emergency Services ◽  
Service System ◽  
Queuing System ◽  
Hospital Service ◽  
Key Factors ◽  
Queuing Model ◽  
Medical Resources ◽  
Proposed Model

The emergency department has an irreplaceable role in the hospital service system because of the characteristics of its emergency services. In this paper, a new patient queuing model with priority weight is proposed to optimize the management of emergency department services. Compared with classical queuing rules, the proposed model takes into consideration the key factors of service and the first-come-first-served queuing rule in emergency services. According to some related queuing indicators, the optimization of emergency services is discussed. Finally, a case study and some compared analysis are conducted to illustrate the practicability of the proposed model.

scholarly journals An optimization model to solve the resource constrained project scheduling problem RCPSP in new product development projects•

DYNA ◽  
2020 ◽  
Vol 87 (212) ◽  
pp. 179-188 ◽  
Author(s):  
Néstor Raúl Ortíz Pimiento ◽  
Francisco Javier Diaz Serna
Keyword(s):  
Product Development ◽  
New Product Development ◽  
Optimization Model ◽  
New Product ◽  
Development Projects ◽  
Analysis Process ◽  
Proposed Model ◽  
Project Scheduling Problem ◽  
The Impact

New product development projects (NPDP) face different risks that may affect the scheduling. In this article, the purpose was to develop an optimization model to solve the RCPSP in NPDP and obtain a robust baseline for the project. The proposed model includes three stages: the identification of the project’s risks, an estimation of activities’ duration, and the resolution of an integer linear program. Two versions of the model were designed and compared in order to select the best one. The first version uses a method to estimate the activities’ duration based on the expected value of the impact of the risks and the second version uses a method based on the judgmental risk analysis process. Finally, the two version of the model were applied to a case study and the best version of the model was identified using a robustness indicator that analyses the start times of the baselines generated.

scholarly journals Unified Framework for Optimal Routing Choice under Guidance Information

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Zhi-yuan Sun ◽  
Yue Li ◽  
Wen-cong Qu ◽  
Tanveer Muhammad
Keyword(s):  
Big Data ◽  
Optimization Model ◽  
Optimal Routing ◽  
Unified Framework ◽  
Proposed Model ◽  
Travel Mode Choice ◽  
Departure Time Choice ◽  
Method Of Successive Averages ◽  
Guidance Information

In order to satisfy the diverse demand of travel service in the context of big data, this paper puts forward a unified framework for optimal routing choice under guidance information. With consideration of the influence of big data, the scenario analysis of routing choice is implemented, and the routing choice under guidance information is discussed. The optimal routing choice problem is abstracted into the collaboration optimization model of travel route choice, departure time choice, and travel mode choice. Based on some basic assumptions, the collaboration optimization model is formulated as a variational inequality model. The method of successive averages is applied to solve the proposed model. A case study is carried out to verify the applicability and reliability of the model and algorithm.

scholarly journals Urban Railway Transit Timetable Optimisation Based on Passenger-and-Trains Matching – A Case Study of Beijing Metro Line

2021 ◽  
Vol 33 (5) ◽  
pp. 671-687
Author(s):  
Junsheng Huang ◽  
Tong Zhang ◽  
Runbin Wei
Keyword(s):  
Genetic Algorithm ◽  
Waiting Time ◽  
Stage Model ◽  
Two Stage ◽  
Left Behind ◽  
Second Stage ◽  
Decision Variables ◽  
Proposed Model ◽  
Railway System

Due to the congested scenarios of the urban railway system during peak hours, passengers are often left behind on the platform. This paper firstly brings a proposal to capture passengers matching different trains. Secondly, to reduce passengers’ total waiting time, timetable optimisation is put forward based on passengers matching different trains. This is a two-stage model. In the first stage, the aim is to obtain a match between passengers and different trains from the Automatic Fare Collection (AFC) data as well as timetable parameters. In the second stage, the objective is to reduce passengers’ total waiting time, whereby the decision variables are headway and dwelling time. Due to the complexity of our proposed model, an MCMC-GASA (Markov Chain Monte Carlo-Genetic Algorithm Simulated Annealing) hybrid method is designed to solve it. A real-world case of Line 1 in Beijing metro is employed to verify the proposed two-stage model and algorithms. The results show that several improvements have been brought by the newly designed timetable. The number of unique matching passengers increased by 37.7%, and passengers’ total waiting time decreased by 15.5%.

scholarly journals Optimization of Construction Duration and Schedule Robustness Based on Hybrid Grey Wolf Optimizer with Sine Cosine Algorithm

Energies ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 215 ◽  
Author(s):  
Mengqi Zhao ◽  
Xiaoling Wang ◽  
Jia Yu ◽  
Lei Bi ◽  
Yao Xiao ◽  
...  
Keyword(s):  
Optimization Model ◽  
Grey Wolf Optimizer ◽  
Grey Wolf ◽  
Power Station ◽  
Starting Time ◽  
Proposed Model ◽  
Efficient Construction ◽  
Sine Cosine Algorithm ◽  
Critical Chain

Construction duration and schedule robustness are of great importance to ensure efficient construction. However, the current literature has neglected the importance of schedule robustness. Relatively little attention has been paid to schedule robustness via deviation of an activity’s starting time, which does not consider schedule robustness via structural deviation caused by the logical relationships among activities. This leads to a possibility of deviation between the planned schedule and the actual situation. Thus, an optimization model of construction duration and schedule robustness is proposed to solve this problem. Firstly, duration and two robustness criteria including starting time deviation and structural deviation were selected as the optimization objectives. Secondly, critical chain method and starting time criticality (STC) method were adopted to allocate buffers to the schedule in order to generate alternative schedules for optimization. Thirdly, hybrid grey wolf optimizer with sine cosine algorithm (HGWOSCA) was proposed to solve the optimization model. The movement directions and speed of grey wolf optimizer (GWO) was improved by sine cosine algorithm (SCA) so that the algorithm’s performance of convergence, diversity, accuracy, and distribution improved. Finally, an underground power station in China was used for a case study, by which the applicability and advantages of the proposed model were proved.

scholarly journals A Case Study on Stratified Settlement and Rebound Characteristics due to Dewatering in Shanghai Subway Station

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Jianxiu Wang ◽  
Tianrong Huang ◽  
Dongchang Sui
Keyword(s):  
Soft Clay ◽  
Subway Station ◽  
Silty Clay ◽  
Metro Station ◽  
Absolute Value ◽  
Sandy Clay ◽  
Centrifugal Model ◽  
Shanghai Metro ◽  
Different Soils

Based on the Yishan Metro Station Project of Shanghai Metro Line number 9, a centrifugal model test was conducted to investigate the behavior of stratified settlement and rebound (SSR) of Shanghai soft clay caused by dewatering in deep subway station pit. The soil model was composed of three layers, and the dewatering process was simulated by self-invention of decompressing devise. The results indicate that SSR occurs when the decompression was carried out, and only negative rebound was found in sandy clay, but both positive and negative rebound occurred in the silty clay, and the absolute value of rebound in sandy clay was larger than in silty clay, and the mechanism of SSR was discussed with mechanical sandwich model, and it was found that the load and cohesive force of different soils was the main source of different responses when decompressed.

scholarly journals A Robust Optimization Model to the Day-Ahead Operation of an Electric Vehicle Aggregator Providing Reliable Reserve

Energies ◽  
2021 ◽  
Vol 14 (22) ◽  
pp. 7456
Author(s):  
Antonio Jiménez-Marín ◽  
Juan Pérez-Ruiz
Keyword(s):  
Robust Optimization ◽  
Real Time ◽  
Electric Vehicle ◽  
Optimization Model ◽  
Linear Problem ◽  
The Other ◽  
Mixed Integer ◽  
Robust Approach ◽  
Proposed Model

This paper presents a robust optimization model to find out the day-ahead energy and reserve to be scheduled by an electric vehicle (EV) aggregator. Energy can be purchased from, and injected to, the distribution network, while upward and downward reserves can be also provided by the EV aggregator. Although it is an economically driven model, the focus of this work relies on the actual availability of the scheduled reserves in a future real-time. To this end, two main features stand out: on one hand, the uncertainty regarding the EV driven pattern is modeled through a robust approach and, on the other hand, a set of non-anticipativity constraints are included to prevent from unavailable future states. The proposed model is posed as a mixed-integer robust linear problem in which binary variables are used to consider the charging, discharging or idle status of the EV aggregator. Results over a 24-h case study show the capability of the proposed model.

scholarly journals A State-Dependent Approximation Method for Estimating Truck Queue Length at Marine Terminals

2021 ◽  
Vol 13 (5) ◽  
pp. 2917
Author(s):  
Wenrui Qu ◽  
Tao Tao ◽  
Bo Xie ◽  
Yi Qi
Keyword(s):  
Approximation Method ◽  
Queue Length ◽  
New Method ◽  
Short Term ◽  
Queuing Model ◽  
State Dependent ◽  
Simulation Based ◽  
Marine Terminals ◽  
Port Congestion

As international trade and freight volumes increase, there is a growing port congestion problem, leading to the long truck queues at US marine terminal gates. To address this problem, some countermeasures have been proposed and implemented for reducing truck queue length at marine terminals. To assess the effectiveness of these countermeasures, a method for accurately estimating terminal gate truck queue length is needed. This study developed a new method, named the state-dependent approximation method, for estimating the truck queue length at marine terminals. Based on the simulation of the truck queuing system, it was found that it takes several hours for the truck queue length to reach its steady state, and neglecting the queue formation (queue dispersion) processes will cause overestimation (underestimation) of truck queue length. The developed model can take into account the queue formation and dispersion processes, and it can be used to estimate the truck queue length caused by short-term oversaturation at marine terminals. For model evaluation, a simulation-based case study was conducted to evaluate the prediction accuracy of the developed model by comparing its results with the simulated queue lengths and the results of other four existing methods, including the fluid flow model, the M/M/S queuing model, and a simulation-based regression model developed a previous study. The evaluation results indicate that the developed model outperformed the other four modeling methods for different states of queue formation and dispersion processes. In addition, this new method can accurately estimate the truck queue length caused by the short-term system oversaturation during peak hours. Therefore, it will be useful for assessing the effectiveness of the countermeasures that are targeted at reducing the peak-hour congestion at marine terminals.

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