Information Technologies and Analytical Models for Strategic Design of Transportation Infrastructure

2017 ◽  
pp. 300-321
Author(s):  
L. Douglas Smith ◽  
Robert M. Nauss ◽  
Liang Xu ◽  
Juan Zhang ◽  
Jan Fabian Ehmke ◽  
...  
Keyword(s):  
Conceptual Framework ◽  
Information Technologies ◽  
Discrete Event ◽  
Decision Rules ◽  
Analytical Models ◽  
Time Varying ◽  
Event Simulation ◽  
Strategic Design ◽  
Heuristic Scheduling ◽  
Multiple Dimensions

Statistical modeling, deterministic optimization, heuristic scheduling procedures, and computer simulation enable the strategic design of service systems while considering complex interdependencies in system operations. Performance on multiple dimensions may be investigated under alternative physical configurations and operating procedures while accommodating time-varying mixes of traffic and demands for service. This paper discusses how analytical tools and a conceptual framework developed for inland waterway transportation were extended and applied to the more complex operating environment of commercial airports. Networks of staged queues constitute the conceptual framework and discrete-event simulation provides the integrating modeling platform. Within the simulation model, statistical models represent time-varying behavior, traffic intensity is adjusted, resources are allocated to system users, traffic is controlled according to prevailing conditions, and decision rules are tested in pursuit of optimal performance.

Analytical Modeling for the Strategic Design of Service Systems

2012 ◽  
Vol 3 (4) ◽  
pp. 1-15
Author(s):  
L. Douglas Smith ◽  
Robert M. Nauss ◽  
Jan Fabian Ehmke ◽  
Dirk Christian Mattfeld
Keyword(s):  
Customer Service ◽  
Service Systems ◽  
Analytical Models ◽  
Conceptual Foundation ◽  
Strategic Design ◽  
Business Logistics ◽  
Heuristic Scheduling ◽  
Multiple Dimensions ◽  
Transportation Service ◽  
Analytical Tools

Systems for transportation, business logistics, production, and customer service must be constructed with consideration of economy, efficiency, user-equity, and flexibility. A proper blend of statistical modeling, deterministic optimization, heuristic scheduling procedures, and computer simulation enables the strategic design of such systems while anticipating the complexity of operations. Performance on multiple dimensions may be investigated for alternative physical configurations and operating procedures while accommodating time-varying mixes of traffic and demands for service. This paper illustrates the blending of analytical tools for an inland waterway transportation service system where staged queues provide the conceptual foundation for operations, and it advocates the use of similar modeling approaches for the strategic design and management of other service systems. For airline traffic at a major commercial airport, where systems of staged queues need to be integrated for optimizing flight and ground operations, the authors suggest the data and analytical models that may be deployed in this more complex environment.

scholarly journals Performance modelling of multi-tier cloud applications using Simpy

2021 ◽  
Author(s):  
Dayle Chettiar
Keyword(s):  
Response Time ◽  
Discrete Event Simulation ◽  
Service Providers ◽  
Discrete Event ◽  
Queueing Network ◽  
Analytical Models ◽  
Performance Modelling ◽  
Event Simulation ◽  
Application Service ◽  
The Mean

Todays cloud deployed applications are mostly multi-tiered. Usually, the first tier consists of an Application Service Providers' (ASPs) web servers, the second tier has application servers and the third tier contains database servers. Tiered architectures are often difficult to evaluate in terms of performance. Existing performance models are very effective in finding the mean performance measures. However, metrics such as response-time percentiles are of greater importance to the end-users since it is more desirable to reduce the variability of a system’s response time, rather than minimizing the mean response time. In this work, a multi-tier application is modeled as an open queuing network of 3-tiers and the response-time percentiles are estimated using discrete event simulation. Here, we assume that each tier is replicated into a number of copies and each copy runs on a separate Virtual Machine (VM). Although simulation models are computationally more expensive as compared to analytical models, they are much more general. The simulation model of this work can be used as decision support for ASPs in order to determine the optimal configuration of VMs for a given workload such that a required response-time percentile is within a given threshold. In this work, Simpy, a discrete event simulation framework, has been used. The results show that as the number of VMs are increased in a 3-tier open queueing network, the overall system performance (i.e. percentiles and mean response times) does not necessarily become better. The results further show that different system configurations containing the same number of VMs, yield different performance depending on the replication level in different tiers.

scholarly journals Analysis of the Dynamics of Rougher Cells on the Basis of Phenomenological Models and Discrete Event Simulation Framework

Metals ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 1454
Author(s):  
Manuel Saldaña ◽  
Purísima Neira ◽  
Víctor Flores ◽  
Carlos Moraga ◽  
Pedro Robles ◽  
...  
Keyword(s):  
Discrete Event Simulation ◽  
Discrete Event ◽  
Theoretical Models ◽  
Analytical Models ◽  
Operational Parameters ◽  
Event Simulation ◽  
Mineral Recovery ◽  
Superficial Gas Velocity ◽  
The Impact ◽  
Over Time

Due to the increase in the amount of copper sulphide minerals processed through concentration processes and the need to improve the efficiency of these production processes, the development of theoretical models is making an important contribution to generating a better understanding of their dynamics, making it possible to identify the optimal conditions for the recovery of minerals, the impact of the independent variables in the responses, and the sensitivity of the recovery to variations in both the input variables and the operational parameters. This paper proposes a method for modeling, sensitizing, and optimizing the mineral recovery in rougher cells using a discrete event simulation (DES) framework and the fitting of analytical models on the basis of operational data from a concentration pilot plant. A sensitivity analysis was performed for low, medium, and high levels of the operative variables and/or parameters. The outcomes of the modeling indicate that the optimum mineral recovery is reached at medium levels of the flow rate of gas, bubble size, turbulence dissipation rate, surface tension, Reynolds number of bubble, bubble–particle contact angle, superficial gas velocity and gas hold-up in the froth zone. Additionally, the optimal response is reached at maximum levels of particle size and density and at minimum levels of bubble speed, fluid kinematic viscosity and fluid density in the sampled range. Finally, the recovery has an asymptotic behavior over time; however, the optimum recovery depends on an economic analysis, examining the marginalization of the response over time in an operational context.

scholarly journals Performance modelling of multi-tier cloud applications using Simpy

2021 ◽  
Author(s):  
Dayle Chettiar
Keyword(s):  
Response Time ◽  
Discrete Event Simulation ◽  
Service Providers ◽  
Discrete Event ◽  
Queueing Network ◽  
Analytical Models ◽  
Performance Modelling ◽  
Event Simulation ◽  
Application Service ◽  
The Mean

Todays cloud deployed applications are mostly multi-tiered. Usually, the first tier consists of an Application Service Providers' (ASPs) web servers, the second tier has application servers and the third tier contains database servers. Tiered architectures are often difficult to evaluate in terms of performance. Existing performance models are very effective in finding the mean performance measures. However, metrics such as response-time percentiles are of greater importance to the end-users since it is more desirable to reduce the variability of a system’s response time, rather than minimizing the mean response time. In this work, a multi-tier application is modeled as an open queuing network of 3-tiers and the response-time percentiles are estimated using discrete event simulation. Here, we assume that each tier is replicated into a number of copies and each copy runs on a separate Virtual Machine (VM). Although simulation models are computationally more expensive as compared to analytical models, they are much more general. The simulation model of this work can be used as decision support for ASPs in order to determine the optimal configuration of VMs for a given workload such that a required response-time percentile is within a given threshold. In this work, Simpy, a discrete event simulation framework, has been used. The results show that as the number of VMs are increased in a 3-tier open queueing network, the overall system performance (i.e. percentiles and mean response times) does not necessarily become better. The results further show that different system configurations containing the same number of VMs, yield different performance depending on the replication level in different tiers.

scholarly journals Discrete-Event Simulation to Model the Thrombolysis Process for Acute Ischemic Stroke Patients at Urban and Rural Hospitals

2021 ◽  
Vol 12 ◽  
Author(s):  
Tessa Bulmer ◽  
David Volders ◽  
John Blake ◽  
Noreen Kamal
Keyword(s):  
Conceptual Framework ◽  
Discrete Event Simulation ◽  
Critical Path ◽  
Discrete Event ◽  
Rural Hospitals ◽  
Time Duration ◽  
Event Simulation ◽  
Maximum Reduction ◽  
The Impact ◽  
Test Scenarios

Background: Effective treatment with tissue plasminogen activator (tPA) critically relies on rapid treatment. Door-to-needle time (DNT) is a key measure of hospital efficiency linked to patient outcomes. Numerous changes can reduce DNT, but they are difficult to trial and implement. Discrete-event simulation (DES) provides a way to model and determine the impact of process improvements.Methods: A conceptual framework was developed to illustrate the thrombolysis process; allowing for treatment processes to be replicated using a DES model developed in ARENA. Activity time duration distributions from three sites (one urban and two rural) were used. Five scenarios, three process changes, and two reductions in activity durations, were simulated and tested. Scenarios were tested individually and in combinations. The primary outcome measure is median DNT. The study goal is to determine the largest improvement in DNT at each site.Results: Administration of tPA in the imaging area resulted in the largest median DNT reduction for Site 1 and Site 2 for individual test scenarios (12.6%, 95% CI 12.4–12.8%, and 8.2%, 95% CI 7.5–9.0%, respectively). Ensuring that patients arriving via emergency medical services (EMS) remain on the EMS stretcher to imaging resulted in the largest median DNT improvement for Site 3 (9.2%, 95% CI 7.9–10.5%). Reducing both the treatment decision time and tPA preparation time by 35% resulted in a 11.0% (95% CI 10.0–12.0%) maximum reduction in median DNT. The lowest median and 90th percentile DNTs were achieved by combining all test scenarios, with a maximum reduction of 26.7% (95% CI 24.5–28.9%) and 17.1% (95% CI 12.5–21.7%), respectively.Conclusions: The detailed conceptual framework clarifies the intra-hospital logistics of the thrombolysis process. The most significant median DNT improvement at rural hospitals resulted from ensuring patients arriving via EMS remain on the EMS stretcher to imaging, while urban sites benefit more from administering tPA in the imaging area. Reducing the durations of activities on the critical path will provide further DNT improvements. Significant DNT improvements are achievable in urban and rural settings by combining process changes with reducing activity durations.

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