Estimation of the Efficiency Indices for Operating the Vertical Transportation Systems

Mapping Intimacies ◽

10.5772/intechopen.94066 ◽

2020 ◽

Author(s):

Yury K. Belyaev ◽

Asaf H. Hajiyev

Keyword(s):

Waiting Time ◽

Transportation Systems ◽

Optimal Number ◽

Control Rule ◽

Average Waiting Time ◽

Control Rules

Various lifts’ systems with different control rules are considered. It is suggested to use the efficiency indexes: customer’s average waiting in lift cabin time and average total time, including the time of delivering the customer to the desired floor. Various control rules are introduced: Odd-Even, where one lift serves only customers in Odd floors and other lift only does that in Even floors Up-Down control rule where one lift serves only customers who are going from the first floor to the destination floor 2, 3,…, k; another lift serves customers from the first floor to the upper floor k + 1, k + 2, …, n. The results of simulation, allowing to compare various control rules relatively to the efficiency indexes, are given. It is introduced an optimal number of lifts, which minimizes number of lifts, minimizing a customer’s average waiting time. For some systems, the method of finding the optimal number of lifts, is suggested. Necessary figures demonstrating the operation of the lifts’ systems and the results of the simulation allow to estimate the efficiency indexes.

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Accurate Estimation of Average Waiting Time in Public Transportation Systems

Transportation Science ◽

10.1287/trsc.2013.0514 ◽

2015 ◽

Vol 49 (2) ◽

pp. 213-222 ◽

Cited By ~ 15

Author(s):

Mohammad Reza Amin-Naseri ◽

Vahid Baradaran

Keyword(s):

Waiting Time ◽

Public Transportation ◽

Transportation Systems ◽

Accurate Estimation ◽

Average Waiting Time ◽

Public Transportation Systems

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Phase Transition in Taxi Dynamics and Impact of Ridesharing

Transportation Science ◽

10.1287/trsc.2019.0915 ◽

2020 ◽

Vol 54 (1) ◽

pp. 250-273

Author(s):

Bo Yang ◽

Shen Ren ◽

Erika Fille Legara ◽

Zengxiang Li ◽

Edward Y. X. Ong ◽

...

Keyword(s):

Phase Boundary ◽

Waiting Time ◽

Road Network ◽

Supply And Demand ◽

Optimal Number ◽

Urban Setting ◽

The Public ◽

Average Waiting Time ◽

Two Phases ◽

City State

We develop a numerical model using both artificial and empirical inputs to analyse taxi dynamics in an urban setting. More specifically, we quantify how the supply and demand for taxi services, the underlying road network, and the public acceptance of taxi ridesharing (TRS) affect the optimal number of taxis for a particular city and commuters’ average waiting time and trip time. Results reveal certain universal features of the taxi dynamics with real-time taxi booking: that there is a well-defined transition between the oversaturated phase when demand exceeds supply and the undersaturated phase when supply exceeds demand. The boundary between the two phases gives the optimal number of taxis a city should accommodate, given the specific demand, road network, and commuter habits. Adding or removing taxis may affect commuter experience very differently in the two phases revealed. In the oversaturated phase, the average waiting time is exponentially affected, whereas in the undersaturated phase it is affected sublinearly. We analyse various factors that can shift the phase boundary and show that an increased level of acceptance for TRS universally shifts the phase boundary by reducing the number of taxis needed. We discuss some of the useful insights for the benefits and costs of TRS, especially how, under certain situations, TRS not only economically benefits commuters but can also save the shared parties in overall travel time by significantly reducing the time commuters spend on waiting for taxis. Simulations also suggest that elementary artificial taxi systems can capture most of the universal features of the taxi dynamics. We give detailed methodologies of the microscopic simulations we employed. The relevance of the assumptions and the overall methodology are also illustrated using comprehensive empirical road network and taxi demand in the city-state of Singapore.

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Measuring Accessibility Based on Improved Impedance and Attractive Functions Using Taxi Trajectory Data

Sustainability ◽

10.3390/su13010112 ◽

2020 ◽

Vol 13 (1) ◽

pp. 112

Author(s):

Helai Huang ◽

Jialing Wu ◽

Fang Liu ◽

Yiwei Wang

Keyword(s):

Waiting Time ◽

Urban Areas ◽

Transportation Systems ◽

Trajectory Data ◽

Peak Period ◽

Important Indicator ◽

Destination Attractiveness ◽

Urban Accessibility ◽

Spatio Temporal ◽

Taxi Trajectory

Accessibility has attracted wide interest from urban planners and transportation engineers. It is an important indicator to support the development of sustainable policies for transportation systems in major events, such as the COVID-19 pandemic. Taxis are a vital travel mode in urban areas that provide door-to-door services for individuals to perform urban activities. This study, with taxi trajectory data, proposes an improved method to evaluate dynamic accessibility depending on traditional location-based measures. A new impedance function is introduced by taking characteristics of the taxi system into account, such as passenger waiting time and the taxi fare rule. An improved attraction function is formulated by considering dynamic availability intensity. Besides, we generate five accessibility scenarios containing different indicators to compare the variation of accessibility. A case study is conducted with the data from Shenzhen, China. The results show that the proposed method found reduced urban accessibility, but with a higher value in southern center areas during the evening peak period due to short passenger waiting time and high destination attractiveness. Each spatio-temporal indicator has an influence on the variation in accessibility.

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Super Smart Optimized Round Robin

Systemic Information System and Informatics Journal ◽

10.29080/systemic.v2i2.110 ◽

2016 ◽

Vol 2 (2) ◽

pp. 19-21

Author(s):

Achmad Teguh Wibowo

Keyword(s):

Waiting Time ◽

Turnaround Time ◽

Round Robin ◽

Priority Scheduling ◽

Average Waiting Time ◽

First Come First Serve ◽

Time Average ◽

Average Turnaround Time

Aspek penting dalam sistem operasi adalah multiprogramming. Multiprogramming adalah proses atau metode yang digunakan untuk mengekssekusi beberapa proses secara bersamaan dalam memori. Tujuan utamanya adalah untuk meminimalkan Average Waiting Time, Average Turnaround Time, dan memaksimalkan penggunaan CPU. Ada berbagai algoritma yang digunakan dalam multiprogramming seperti First Come First Serve (FCFS), Shortest Job First (SJF), Priority Scheduling (PS) dan Round Robin(RR). Diantara semua itu yang paling sering digunakan adalah Round Robin. Round Robin merupakan algoritma penjadwalan yang optimal dengn sistem timeshared. Dalam RR, waktu kuantum bersifat statis dan algoritma ini bergantung pada besarnya kuantum yang dipilih/digunakan. Kuantum inilah yang berpengaruh pada Average Waiting Time dan Average Turnaround Time nantinya. Tujuan dari makalah ini adalah mengusulkan algoritma yang lebih baik daripada Round Robin sederhana dan Smart Optimized Round Robin sebelumnya.

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Inter-Machine Exchange of Real Time in Distributed Computer Systems

10.51130/graphicon-2020-2-4-50 ◽

2020 ◽

pp. short50-1-short50-8

Author(s):

Vladimir Bogatyrev ◽

Stanislav Bogatyrev ◽

Anatoly Bogatyrev

Keyword(s):

Real Time ◽

Analytical Model ◽

Waiting Time ◽

Computer Systems ◽

Delivery Time ◽

Network Nodes ◽

Average Waiting Time ◽

Service Delays ◽

Distributed Computer Systems

The possibilities of increasing the likelihood of timely service and reducing the average waiting time for requests for inter-machine exchange in distributed real-time computer systems are investigated. The analyzed effect is achieved as a result of redundant multi-way transmissions of packets that are critical to delays, which provide for the replication of transmitted packets with the task for each replica of the path (route) of the sequential passage of network nodes. The condition for the timeliness of the reserved transmissions is that the accumulated waiting in the queues of the nodes making up the path, at least for one of the replicas, does not exceed the maximum permissible time. An analytical model is proposed for estimating the average delays of multi-path redundant transmissions, when determined by the average delivery time of the first of the replicas transmitted in different ways. For requests critical to service delays, the influence of the frequency of reservation (replication) of requests on the probability of their timely service and the average waiting time accumulated at the nodes of the path for the replica delivered first was analyzed.

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Scheduling Schemes in Dynamic Multilevel Packet Scheduling in WSN

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.b1714.078219 ◽

2019 ◽

Vol 8 (2) ◽

pp. 3800-3804

Keyword(s):

Real Time ◽

Waiting Time ◽

Packet Scheduling ◽

Turnaround Time ◽

Priority Level ◽

Average Waiting Time ◽

Level 3 ◽

Overall Performance ◽

The Individual ◽

Priority Levels

As focusing on the scheduling schemes, there are many scheduling schemes for multilevel. So the paper is concentrating to compare the scheduling schemes and producing the average waiting time and turnaround time. If it is minimized then the overall performance may shoot up. In this paper comparison is done between three scheduling schemes Enhanced Dynamic Multilevel Packet scheduling (EDMP), Circular Wait Dynamic Multilevel Packet scheduling (CW-DMP) and Starvation-Free Dynamic Multilevel Packet scheduling (SF-DMP). In all the above schemes there are three priority levels say priority level 1(Pr1), priority level 2(Pr2) and priority level 3(Pr3). Pr1 will comprise the real time tasks, Pr2 containing the non real time remote tasks and non real time local tasks are there in Pr3. In each and every scheme, each and every priority level will be using the individual scheduling technique to schedule the tasks. Also the comparison is done based on waiting time and the turnaround time of the task thereby the average waiting time and the average turnaround time are calculated.

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EP.WE.727Upper GI Surgery Clinic Referrals; Can We Improve the Patient Experience?

British Journal of Surgery ◽

10.1093/bjs/znab308.088 ◽

2021 ◽

Vol 108 (Supplement_7) ◽

Author(s):

Mohamed Abouelazayem ◽

Raluca Belchita

Keyword(s):

Patient Experience ◽

Waiting Time ◽

Waiting Times ◽

Patient Records ◽

Electronic Patient Records ◽

Post Discharge ◽

Average Waiting Time ◽

Upper Gi

Abstract Aim To review the new referrals to the Upper GI surgery clinic for appropriateness, investigations requested, and waiting times and to identify potential pathways to reduce waiting times and improve the patient experience. Method Patients who attended the UGI clinic over 2 months period were identified. Data were collected from GP referrals and Electronic Patient Records. Follow up, post-discharge appointments, and Did Not Attends were excluded. Data collected included time from referral to first clinic, symptoms, investigations requested, suitability for a pathway, and appropriateness of referral. A first clinic outcome was concluded from reading the GP referral, there were 5 outcomes to choose from; direct to another specialty, discharge back to GP, clinic, surgery, pre-investigate and clinic. Results 147 referrals were analysed. The average waiting time from referral to the first clinic was 51 days (range 7-119 days). 73% of the referrals were GP referrals and 27% from other specialties. The most common referral was for gallstones and the most common 2 outcomes were Pre-investigate and surgery. Conclusion Most of the investigations and outcomes suggested from the project were the same as those from clinic letters. The following pathways can be developed to cut waiting times and costs for the trust:

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The Study on Production Performances of Part Transporter in Flexible Manufacturing System by Using Simulation Method

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.576.714 ◽

2012 ◽

Vol 576 ◽

pp. 714-717

Author(s):

Mohammad Iqbal ◽

Muhammad Ridwan Andi Purnomo ◽

Muhammad Ammar Bin Mohd Imra ◽

Mohamed Konneh ◽

A.N. Mustafizul Karim

Keyword(s):

Waiting Time ◽

Flexible Manufacturing ◽

Material Handling ◽

Manufacturing System ◽

Flexible Manufacturing System ◽

Arrival Rate ◽

Simulation Method ◽

Simulation Software ◽

Average Waiting Time ◽

Processing Times

Material handling is one of major components in Flexible Manufacturing System (FMS). Any improvement of material handling capability is to affect the performance of the whole system. This paper discusses the simulation study on the effect of part arrival rate and dispatching rules to the average waiting time and production rate of the FMS. The facilities of the system were modeled into simulation environment by using Arena Simulation Software. The production parameters such as machine processing times, part transportation speed and type of products were put into the model to represent the behaviors of the real system. Two rules have been considered in the study, i. e. first come first served (FCFS), and shortest processing time (SPT). Average waiting time and productivity were taken into account as performance measures of the system. The result of the study showed that SPT rule gives shorter average waiting time and higher productivity. Based on this result, the SPT rules would be used to control part transporter in order to have a better performance of the FMS.

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