An agent-based simulation model for analyzing the impact of asymmetric passenger demand on taxi service

2010 ◽  
Vol 15 (1) ◽  
pp. 187-195 ◽  
Author(s):  
Hyunmyung Kim ◽  
Inchul Yang ◽  
Keechoo Choi
Keyword(s):  
Simulation Model ◽  
Agent Based Simulation ◽  
Agent Based ◽  
Passenger Demand ◽  
Taxi Service ◽  
The Impact

scholarly journals Application of Agent-based Modeling for Cultural Information-based Decisions Making

2020 ◽  
Vol 88 ◽  
pp. 8-28
Author(s):  
Rimvydas Laužikas ◽  
Darius Plikynas ◽  
Vytautas Dulskis ◽  
Leonidas Sakalauskas ◽  
Arūnas Miliauskas
Keyword(s):  
Social Capital ◽  
Simulation Model ◽  
Cultural Participation ◽  
Agent Based Simulation ◽  
Research Issues ◽  
Agent Based ◽  
Cultural Events ◽  
The Social ◽  
Cultural Processes ◽  
The Impact

The impact of cultural processes on personal and social changes is one of the important research issues not only in contemporary social sciences but also for simulation of future development scenarios and evidence-based policy decision making. In the context of the theoretical concept of cultural values, based on the system theory and theory of social capital, the impact of cultural events could be analyzed and simulated by focussing on the construction/deconstruction of social capital, which takes place throughout the actor’s cultural participation. The main goal of this research is the development of measuring metrics, and agent-based simulation model aimed at investigation of the social impact of cultural processes.  This paper provides new insights of modeling the social capital changes in a society and its groups, depending on cultural participation. The proposed measurement metrics provide the measurement facility of three key components: actors, cultural events and events flow and social capital. It provides the initial proof of concept simulation results, - simplified agent-based simulation model showcase. The NetLogo MAS platform is used as a simulation environment.  

Agent Based Model to Analyze Consumer Behavior in Consuming the Electricity Energy

2015 ◽  
Vol 72 (4) ◽  
Author(s):  
Erma Suryani ◽  
Rully Agus Hendrawan ◽  
Umi Salama ◽  
Lily Puspa Dewi
Keyword(s):  
Consumer Behavior ◽  
Simulation Model ◽  
Environmental Awareness ◽  
Electricity Consumption ◽  
Point Of View ◽  
Agent Based Model ◽  
Agent Based Simulation ◽  
Agent Based ◽  
Save Energy ◽  
The Impact

Several studies have been conducted regarding save energy in consuming the electricity through the simple changes in routines and habits. In the case of electricity consumption, consumer behavior might influenced by several factors such as consumer profession, season, and environmental awareness. In this paper, we developed an Agent Based Model (ABM) to analyze the behavior of different agents in consuming the electricity energy for each type of profession (agent) as well as their interaction with the environment. This paper demonstrates a prototype agent based simulation model to estimate the electricity consumption based on the existing condition and some scenarios to reduce the electricity consumption from consumer point of view. From the scenario results, we analyzed the impact of the save energy to increase the electrification ratio. 

scholarly journals Investigation and prediction of open source software evolution using automated parameter mining for agent-based simulation

2021 ◽  
Vol 28 (1) ◽  
Author(s):  
Daniel Honsel ◽  
Verena Herbold ◽  
Stephan Waack ◽  
Jens Grabowski
Keyword(s):  
Simulation Model ◽  
Software Evolution ◽  
Prediction Models ◽  
Structural Evolution ◽  
Simulation Models ◽  
Agent Based Simulation ◽  
Specific Data ◽  
Agent Based ◽  
Project Data ◽  
The Impact

AbstractTo guide software development, the estimation of the impact of decision making on the development process can be helpful in planning. For this estimation, often prediction models are used which can be learned from project data. In this paper, an approach for the usage of agent-based simulation for the prediction of software evolution trends is presented. The specialty of the proposed approach lies in the automated parameter estimation for the instantiation of project-specific simulation models. We want to assess how well a baseline model using average (commit) behavior of the agents (i.e., the developers) performs compared to models where different amount of project-specific data is fed into the simulation model. The approach involves the interplay between the mining framework and simulation framework. Parameters to be estimated include, e.g., file change probabilities of developers and the team constellation reflecting different developer roles. The structural evolution of software projects is observed using change coupling graphs based on common file changes. For the validation of simulation results, we compare empirical with simulated results. Our results showed that an average simulation model can mimic general project growth trends like the number of commits and files well and thus, can help project managers in, e.g., controlling the onboarding of developers. Besides, the simulated co-change evolution could be improved significantly using project-specific data.

scholarly journals 2418. Determining the Impact of Visitor Contact Precautions on Hospital-Onset Clostridioides difficile Infection Rates: An Agent-Based Simulation Modeling Approach

2019 ◽  
Vol 6 (Supplement_2) ◽  
pp. S835-S835
Author(s):  
Oguzhan Alagoz ◽  
Elizabeth Scaria ◽  
Anna K Barker ◽  
Nasia Safdar
Keyword(s):  
Hand Hygiene ◽  
Simulation Model ◽  
Healthcare Worker ◽  
Healthcare Workers ◽  
Agent Based Simulation ◽  
Environmental Cleaning ◽  
Agent Based ◽  
Contact Precautions ◽  
Clostridioides Difficile ◽  
The Impact

Abstract Background Visitor contact precautions (VCP) have been suggested to reduce the transmission of Clostridiodes difficile at healthcare institutions. However, there are no data describing the impact of VCP on hospital-acquired C. difficile infection (HO-CDI) rates. Enforcing VCP for CDI control is also controversial, as VCP are poorly implemented and highly variable. Methods We developed an agent-based simulation model of C. difficile transmission at a model 200-bed acute-care adult hospital. Our agent-based simulation model represented interactions among the physicians, nurses, patients, visitors, and physical environment. We used the agent-based simulation model to evaluate the impact of VCP on reducing HO-CDI considering many different hospital settings and various assumptions on patient susceptibility, adherence rates to other infection control practices, interactions between healthcare workers and patients. Results VCP did not reduce the CDC-defined HO-CDI rates by more than 1% in any of the tested scenarios and hospital settings. Increasing the adherence of hand hygiene of healthcare workers to 56% from a baseline estimate of 55%, or compliance to room cleaning to 50% from a baseline estimate of 47% have led to higher rates of reduction in CDI compared with VCP. Conclusion This is the first mathematical model to quantify the reduction in HO-CDI with VCP. The agent-based simulation model suggests that the impact of VCP on hospital-onset CDI is minimal and hospitals can achieve a higher rate of reduction for HO-CDI by implementing other interventions such as healthcare worker hand hygiene, environmental cleaning and healthcare worker contact precautions. Further studies are needed to evaluate the impact of VCP on C. difficile colonization in community. Disclosures All authors: No reported disclosures.

scholarly journals Impact of Timing of and Adherence to Social Distancing Measures on COVID-19 Burden in the US: A Simulation Modeling Approach

2020 ◽  
Author(s):  
Oguzhan Alagoz ◽  
Ajay K. Sethi ◽  
Brian W. Patterson ◽  
Matthew Churpek ◽  
Nasia Safdar
Keyword(s):  
New York ◽  
Simulation Model ◽  
Disease Transmission ◽  
Major Effect ◽  
Agent Based Simulation ◽  
Population Demographics ◽  
Agent Based ◽  
Social Distancing ◽  
The People ◽  
The Impact

ABSTRACTBackgroundAcross the U.S., various social distancing measures were implemented to control COVID-19 pandemic. However, there is uncertainty in the effectiveness of such measures for specific regions with varying population demographics and different levels of adherence to social distancing. The objective of this paper is to determine the impact of social distancing measures in unique regions.MethodsWe developed COVid-19 Agent-based simulation Model (COVAM), an agent-based simulation model (ABM) that represents the social network and interactions among the people in a region considering population demographics, limited testing availability, imported infections from outside of the region, asymptomatic disease transmission, and adherence to social distancing measures. We adopted COVAM to represent COVID-19-associated events in Dane County, Wisconsin, Milwaukee metropolitan area, and New York City (NYC). We used COVAM to evaluate the impact of three different aspects of social distancing: 1) Adherence to social distancing measures; 2) timing of implementing social distancing; and 3) timing of easing social distancing.ResultsWe found that the timing of social distancing and adherence level had a major effect on COVID-19 occurrence. For example, in NYC, implementing social distancing measures on March 5, 2020 instead of March 12, 2020 would have reduced the total number of confirmed cases from 191,984 to 43,968 as of May 30, whereas a 1-week delay in implementing such measures could have increased the number of confirmed cases to 1,299,420. Easing social distancing measures on June 1, 2020 instead of June 15, 2020 in NYC would increase the total number of confirmed cases from 275,587 to 379,858 as of July 31.ConclusionThe timing of implementing social distancing measures, adherence to the measures, and timing of their easing have major effects on the number of COVID-19 cases.Primary Funding SourceNational Institute of Allergy and Infectious Diseases Institute

scholarly journals Process Modeling and Simulation of Tableting—An Agent-Based Simulation Methodology for Direct Compression

Pharmaceutics ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 996
Author(s):  
Niels Lasse Martin ◽  
Ann Kathrin Schomberg ◽  
Jan Henrik Finke ◽  
Tim Gyung-min Abraham ◽  
Arno Kwade ◽  
...  
Keyword(s):  
Raw Materials ◽  
Pilot Scale ◽  
Physical Models ◽  
Agent Based Simulation ◽  
Validation Data ◽  
Agent Based ◽  
Industrial Processing ◽  
Digital Twins ◽  
Product And Process ◽  
The Impact

In pharmaceutical manufacturing, the utmost aim is reliably producing high quality products. Simulation approaches allow virtual experiments of processes in the planning phase and the implementation of digital twins in operation. The industrial processing of active pharmaceutical ingredients (APIs) into tablets requires the combination of discrete and continuous sub-processes with complex interdependencies regarding the material structures and characteristics. The API and excipients are mixed, granulated if required, and subsequently tableted. Thereby, the structure as well as the properties of the intermediate and final product are influenced by the raw materials, the parametrized processes and environmental conditions, which are subject to certain fluctuations. In this study, for the first time, an agent-based simulation model is presented, which enables the prediction, tracking, and tracing of resulting structures and properties of the intermediates of an industrial tableting process. Therefore, the methodology for the identification and development of product and process agents in an agent-based simulation is shown. Implemented physical models describe the impact of process parameters on material structures. The tablet production with a pilot scale rotary press is experimentally characterized to provide calibration and validation data. Finally, the simulation results, predicting the final structures, are compared to the experimental data.

Modeling Consumer Decisions on Returning End-of-Use Products Considering Design Features and Consumer Interactions: An Agent Based Simulation Approach

2015 ◽  
Author(s):  
Ardeshir Raihanian Mashhadi ◽  
Behzad Esmaeilian ◽  
Sara Behdad
Keyword(s):  
Electronic Waste ◽  
Peer Pressure ◽  
Waste Stream ◽  
Contributing Factors ◽  
Agent Based Simulation ◽  
Design Features ◽  
Agent Based ◽  
Consumer Decisions ◽  
Take Back ◽  
The Impact

As electronic waste (e-waste) becomes one of the fastest growing environmental concerns, remanufacturing is considered as a promising solution. However, the profitability of take back systems is hampered by several factors including the lack of information on the quantity and timing of to-be-returned used products to a remanufacturing facility. Product design features, consumers’ awareness of recycling opportunities, socio-demographic information, peer pressure, and the tendency of customer to keep used items in storage are among contributing factors in increasing uncertainties in the waste stream. Predicting customer choice decisions on returning back used products, including both the time in which the customer will stop using the product and the end-of-use decisions (e.g. storage, resell, through away, and return to the waste stream) could help manufacturers have a better estimation of the return trend. The objective of this paper is to develop an Agent Based Simulation (ABS) model integrated with Discrete Choice Analysis (DCA) technique to predict consumer decisions on the End-of-Use (EOU) products. The proposed simulation tool aims at investigating the impact of design features, interaction among individual consumers and socio-demographic characteristics of end users on the number of returns. A numerical example of cellphone take-back system has been provided to show the application of the model.

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