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.

A Simulation-based Approach to Optimize the Execution Time and Minimization of Average Waiting Time Using Queuing Model in Cloud Computing Environment

2016 ◽  
Vol 6 (2) ◽  
pp. 743
Author(s):  
Souvik Pal ◽  
Prasant Kumar Pattnaik
Keyword(s):  
Cloud Computing ◽  
Waiting Time ◽  
Execution Time ◽  
Queue Length ◽  
Service Providers ◽  
Business Systems ◽  
It Industry ◽  
Queuing Model ◽  
Simulation Based ◽  
Time Minimization

Cloud computing is the emerging domain in academia and IT Industry. It is a business framework for delivering the services and computing power on-demand basis. Cloud users have to pay the service providers based on their usage. For enterprises, cloud computing is the worthy of consideration and they try to build business systems with lower costs, higher profits and quality-of-service. Considering cost optmization, service provider may initially try to use less number of CPU cores and data centers. For that reason, this paper deals with CloudSim simulation tool which has been utilized for evaluating the number of CPU cores and execution time. Minimization of waiting time is also a considerable issue. When a large number of jobs are requested, they have to wait for getting allocated to the servers which in turn may increase the queue length and also waiting time. This paper also deals with queuing model with multi-server and finite capacity to reduce the waiting time and queue length.

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.

VISSIM Simulation-Based Traffic Optimization Solution: Case Study in Nanjing, China

2014 ◽  
Vol 641-642 ◽  
pp. 833-838 ◽  
Author(s):  
Bin Bin Yang ◽  
Jian Zhang ◽  
Yong Kai Hu ◽  
Hao Miao Wang ◽  
Lu Song
Keyword(s):  
Simulation Model ◽  
Traffic Congestion ◽  
Queue Length ◽  
Traffic Situation ◽  
Green Band ◽  
Simulation Based ◽  
Traffic Optimization ◽  
Real Traffic ◽  
Better Than

On the basis of traffic survey, an improved simulation model is established by using the VISSIM to simulate the traffic running operation of the Beijing West Road in Nanjing, China. By considering the evaluation of the real traffic situation, two optimized solutions are proposed to relieve the traffic congestion which is caused by the traffic tidal phenomenon. A simulation model is built, with the help from the two optimized solutions. Data about travel time, queue length, vehicular delay, vehicular stop delay and number of stops are generated. Via analyzing and comparing these significant indicators, the results show that the proposed solution is better than the solution of Green-band Traffic. The VISSIM simulation-based optimization solution in this paper is effective.

scholarly journals A Simulation-based Approach to Optimize the Execution Time and Minimization of Average Waiting Time Using Queuing Model in Cloud Computing Environment

2016 ◽  
Vol 6 (2) ◽  
pp. 743
Author(s):  
Souvik Pal ◽  
Prasant Kumar Pattnaik
Keyword(s):  
Cloud Computing ◽  
Waiting Time ◽  
Execution Time ◽  
Queue Length ◽  
Service Providers ◽  
Business Systems ◽  
It Industry ◽  
Queuing Model ◽  
Simulation Based ◽  
Time Minimization

Cloud computing is the emerging domain in academia and IT Industry. It is a business framework for delivering the services and computing power on-demand basis. Cloud users have to pay the service providers based on their usage. For enterprises, cloud computing is the worthy of consideration and they try to build business systems with lower costs, higher profits and quality-of-service. Considering cost optmization, service provider may initially try to use less number of CPU cores and data centers. For that reason, this paper deals with CloudSim simulation tool which has been utilized for evaluating the number of CPU cores and execution time. Minimization of waiting time is also a considerable issue. When a large number of jobs are requested, they have to wait for getting allocated to the servers which in turn may increase the queue length and also waiting time. This paper also deals with queuing model with multi-server and finite capacity to reduce the waiting time and queue length.

STRATEGI KOMUNIKASI CROWDFUNDING PADA KOLASE.COM

2019 ◽  
Vol 2 (2) ◽  
pp. 177-187
Author(s):  
Venessa Agusta Gogali ◽  
Fajar Muharam ◽  
Syarif Fitri
Keyword(s):  
Social Media ◽  
Communication Strategies ◽  
Communication Strategy ◽  
New Method ◽  
Media Communication ◽  
Social Activists ◽  
Social Media Communication

Crowdfunding is a new method in fundraising activities based online. Moreover, the level of penetration of social media to the community is increasingly high. This makes social activists and academics realize that it is important to study social media communication strategies in crowdfunding activities. There is encouragement to provide an overview of crowdfunding activities. So the author conducted a research on "Crowdfunding Communication Strategy Through Kolase.com Through Case Study on the #BikinNyata Program Through the Kolase.com Website that successfully achieved the target. Keywords: Strategic of Communication, Crowdfunding, Social Media.

Emplacing Berlin: Digital Itineraries and Short-term Study Abroad in the City

2018 ◽  
Vol 12 (1) ◽  
pp. 26-36 ◽  
Author(s):  
Richard B. Apgar
Keyword(s):  
Study Abroad ◽  
Urban Landscape ◽  
Physical Space ◽  
Short Term ◽  
Study Abroad Programs ◽  
Term Study ◽  
Digital Maps ◽  
Short Term Study ◽  
The City

As destination of choice for many short-term study abroad programs, Berlin offers students of German language, culture and history a number of sites richly layered with significance. The complexities of these sites and the competing narratives that surround them are difficult for students to grasp in a condensed period of time. Using approaches from the spatial humanities, this article offers a case study for enhancing student learning through the creation of digital maps and itineraries in a campus-based course for subsequent use during a three-week program in Berlin. In particular, the concept of deep mapping is discussed as a means of augmenting understanding of the city and its history from a narrative across time to a narrative across the physical space of the city. As itineraries, these course-based projects were replicated on site. In moving from the digital environment to the urban landscape, this article concludes by noting meanings uncovered and narratives formed as we moved through the physical space of the city.

The impact of Airbnb on a non-touristic city. A Case study of short-term rentals in Santa Cruz de Tenerife (Spain)

Erdkunde ◽  
2020 ◽  
Vol 74 (3) ◽  
pp. 191-204
Author(s):  
Marcus Hübscher ◽  
Juana Schulze ◽  
Felix zur Lage ◽  
Johannes Ringel
Keyword(s):  
Santa Cruz ◽  
Short Term ◽  
Rental Market ◽  
Rural Space ◽  
Use Of Data ◽  
Web Scraping ◽  
Per Capita ◽  
Per Se ◽  
The Impact

Short-term rentals such as Airbnb have become a persistent element of today’s urbanism around the globe. The impacts are manifold and differ depending on the context. In cities with a traditionally smaller accommodation market, the impacts might be particularly strong, as Airbnb contributes to ongoing touristification processes. Despite that, small and medium-sized cities have not been in the centre of research so far. This paper focuses on Santa Cruz de Tenerife as a medium-sized Spanish city. Although embedded in the touristic region of the Canary Islands, Santa Cruz is not a tourist city per se but still relies on touristification strategies. This paper aims to expand the knowledge of Airbnb’s spatial patterns in this type of city. The use of data collected from web scraping and geographic information systems (GIS) demonstrates that Airbnb has opened up new tourism markets outside of the centrally established tourist accommodations. It also shows that the price gap between Airbnb and the housing rental market is broadest in neighbourhoods that had not experienced tourism before Airbnb entered the market. In the centre the highest prices and the smallest units are identified, but two peripheral quarters stand out. Anaga Mountains, a natural and rural space, has the highest numbers of Airbnb listings per capita. Suroeste, a suburban quarter, shows the highest growth rates on the rental market, which implies a linkage between Airbnb and suburbanization processes.

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