B. Celik, P. V. Gorp, André Snoeck, R. V. Riet, P. D. Winter, A. Wilbik
{"title":"A model based simulation toolkit for evaluating renal replacement policies","authors":"B. Celik, P. V. Gorp, André Snoeck, R. V. Riet, P. D. Winter, A. Wilbik","doi":"10.1109/WSC.2017.8248002","DOIUrl":"https://doi.org/10.1109/WSC.2017.8248002","url":null,"abstract":"Renal failure concerns progressive loss of kidney function. Renal Replacement Therapy (RRT) is a costly, long-running process that includes several decision points in different stages. Small changes in the protocol can impact significantly the expenditures and healthcare outcomes. Unfortunately, policy makers have very little support for benchmarking improvement alternatives. The existing models are designed to fit certain applications with preset parameters and design choices which do not match with the requirements of a policy analysis. A generic approach is required to analyze the effects of different design options adjustable to finer scales. To remedy this, this paper describes a novel toolkit for evaluating renal replacement policies, containing a parametrized colored Petri-Net which can be configured for the specifics of local settings. The model is made available for open access to overcome the non-replicability issue of existing models.","PeriodicalId":145780,"journal":{"name":"2017 Winter Simulation Conference (WSC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127981491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Improving prediction from stochastic simulation via model discrepancy learning","authors":"H. Lam, Xinyu Zhang, M. Plumlee","doi":"10.5555/3242181.3242331","DOIUrl":"https://doi.org/10.5555/3242181.3242331","url":null,"abstract":"Stochastic simulation is an indispensable tool in operations and management applications. However, simulation models are only approximations to reality, and often bear discrepancies with the generating processes of real output data. We investigate a framework to statistically learn these discrepancies under the presence of data on past implemented system configurations, which allows us to improve prediction using simulation models. We focus on the case of general continuous output data that generalizes previous work. Our approach utilizes (a combination of) regression analysis and optimization formulations constrained on suitable summary statistics. We demonstrate our approach with a numerical example.","PeriodicalId":145780,"journal":{"name":"2017 Winter Simulation Conference (WSC)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115958388","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
B. Tivnan, M. Koehler, David M. Slater, J. Veneman, Brendan F. Tivnan
{"title":"Towards a model of the U.S. stock market: How important is the securities information processor?","authors":"B. Tivnan, M. Koehler, David M. Slater, J. Veneman, Brendan F. Tivnan","doi":"10.1109/WSC.2017.8247865","DOIUrl":"https://doi.org/10.1109/WSC.2017.8247865","url":null,"abstract":"Both the scientific community and the popular press have paid much attention to the speed of the Securities Information Processor — the data feed consolidating all trades and quotes across the US stock market. Rather than the speed of the Securities Information Processor, or SIP, we focus here on its importance to efficient, price discovery. Via extensions to a previous market model, we experiment with four different coupling mechanisms which operate across the US stock market. Of the four, we find that the SIP contributes most to efficient price discovery.","PeriodicalId":145780,"journal":{"name":"2017 Winter Simulation Conference (WSC)","volume":"23 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113963910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The computer simulation archive: Development and current contents","authors":"R. Nance, G. Thayer","doi":"10.1109/WSC.2017.8247797","DOIUrl":"https://doi.org/10.1109/WSC.2017.8247797","url":null,"abstract":"The development history of the Computer Simulation Archive is described from its inception in 1998 to the present. An overlap of visions among the creators produces an asset for the simulation community and the North Carolina State University Libraries. Collections donated over this period have produced impressive growth. Usage statistics show a steady increase in access, and the simulation endowment has nearly tripled over the past six years. The commitment of the North Carolina State University Libraries staff and the strong, consistent support of the simulation community are the key factors in this record of success.","PeriodicalId":145780,"journal":{"name":"2017 Winter Simulation Conference (WSC)","volume":"223 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132344882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Oussama Batata, V. Augusto, S. Ebrahimi, Xiaolan Xie
{"title":"Performance evaluation of respite care services through multi-agent based simulation","authors":"Oussama Batata, V. Augusto, S. Ebrahimi, Xiaolan Xie","doi":"10.1109/WSC.2017.8248013","DOIUrl":"https://doi.org/10.1109/WSC.2017.8248013","url":null,"abstract":"Caregivers of patients with chronic diseases are undergoing a daily burnout in their lives. Although respite care seems a promising solution, no quantitative analysis has yet been provided to demonstrate its positive impact. In this article, we propose (i) a new model of caregivers' burnout evolution based on Markov chain and machine learning to model health state evolution, and (ii) a multi-agent based simulation approach to describe the burnout evolution of caregivers and the impact of respite structures on the system. Optimal capacity of respite structures is obtained through a design of experiment. Several management strategies are also tested (collaboration between structures, reservation of beds for emergent cases). Key performance indicators considered are quality of service and costs. Results show a positive impact of respite services on both quality of service and costs. The model also show a trade-off between quality of service and costs when bed reservation policies are used.","PeriodicalId":145780,"journal":{"name":"2017 Winter Simulation Conference (WSC)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133892019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Artificial neural network models for building energy prediction","authors":"K. Ahn, Cheol-Soo Park","doi":"10.1109/WSC.2017.8247996","DOIUrl":"https://doi.org/10.1109/WSC.2017.8247996","url":null,"abstract":"There is a national need for a quick and easy building energy performance assessment system of existing buildings, without resorting to dynamic building energy simulation tools which usually require significant cost, time and expertise. In this study, the authors report the development of a building energy profiling system which is based on Artificial Neural Network (ANN) models. The ANN models were made by a series of EnergyPlus pre-simulations sampled by a Monte Carlo technique. The MBE and CVRMSE between EnergyPlus and ANN models are 1.53% and 7.82%, respectively. It is concluded that the profiling system requires minimalistic inputs and provides accurate energy performance assessment of a given building.","PeriodicalId":145780,"journal":{"name":"2017 Winter Simulation Conference (WSC)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133949423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Data-driven simulation-based model for planning roadway operation and maintenance projects","authors":"Emad Mohamed, Parinaz Jafari, M. Siu, S. Abourizk","doi":"10.1109/WSC.2017.8248049","DOIUrl":"https://doi.org/10.1109/WSC.2017.8248049","url":null,"abstract":"Snow removal operations are required to maintain roadway safety during snowy winter conditions. Reliable plans outlining the dispatching of plow trucks must be made to deliver snow removal operations on time and within budget. Historical project performance data can be used to inform and facilitate decision-making processes associated with snow removal operations. This research proposes a data-driven simulation framework for planning snow removal projects considering weather and truck-related data collected by real-time sensors. An in-house developed simulation engine, Simphony.Net, is used to simulate operations based on input information extracted from mined sensor data. This model is capable of simulating plow operations to facilitate planning at both an operational and real-time level. What-if scenarios can be generated to simulate, predict, and optimize project and resource performance. A case study conducted in Alberta, Canada is presented to illustrate the practical application of the proposed method.","PeriodicalId":145780,"journal":{"name":"2017 Winter Simulation Conference (WSC)","volume":"210 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134000843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Information blackouts in a multi-echelon supply chain simulation","authors":"Elizabeth Rasnick, Dean C. Chatfield","doi":"10.1109/WSC.2017.8248059","DOIUrl":"https://doi.org/10.1109/WSC.2017.8248059","url":null,"abstract":"Information blackouts, defined as sudden and short-duration failures of the information flow in a supply chain, amplify the bullwhip effect in supply chains. We develop a discrete-event simulation of a multi-echelon supply chain, utilizing Rockwell Automation's Arena software tool, to investigate this phenomenon. We investigate inventory order history blackouts of three different durations (1, 2, and 3 time periods). Based on the increased bullwhip effect observed as the result of an information blackout, managers may decide to “wait out” the amplification or to use an estimate to replace the missing inventory order history by utilizing the last known value. The latter choice employs the common manager's heuristic of trusting the recent past to be the best predictor of the future. Our results provide supporting evidence for such managerial decisions.","PeriodicalId":145780,"journal":{"name":"2017 Winter Simulation Conference (WSC)","volume":"141 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131905078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Stochastic co-kriging for steady-state simulation metamodeling","authors":"Xi Chen, S. Hemmati, Feng Yang","doi":"10.5555/3242181.3242326","DOIUrl":"https://doi.org/10.5555/3242181.3242326","url":null,"abstract":"In this paper we present the stochastic co-kriging methodology (SCK) for approximating a steady-state mean response surface based on outputs from both long and short simulation replications performed at selected design points. We provide details on how to construct an SCK metamodel, perform parameter estimation, and make prediction via SCK. We demonstrate numerically that SCK holds the promise of providing more accurate prediction results at no additional computational effort by only externally adjusting the simulation runlength and number of independent replications of simulations through the experimental design of the simulation study.","PeriodicalId":145780,"journal":{"name":"2017 Winter Simulation Conference (WSC)","volume":"8 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132891966","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Construction objects recognition in framework of CPS","authors":"Y. Srewil, R. Scherer","doi":"10.1109/WSC.2017.8247976","DOIUrl":"https://doi.org/10.1109/WSC.2017.8247976","url":null,"abstract":"Recent breakthroughs in BIM and ADC technologies promise innovative solutions to bridge the information gaps between the digital models and real construction site. These solutions promote the collaboration between digital, spatial and physical construction. Cyber-physical systems offer a tight integration between real physical and virtual “cyber” models. This collaborative approach supports the digital transformation in construction domain. A cyber-physical framework is proposed to provide consistent relationships and allow bidirectional data flow. In the framework the recognition of objects successes by linking physical objects to the digital product models using RFID. Next, these objects are equipped with global positions data and pinned to semantic and functional enrichment construction places. The results are objects at a level of “smartness” with enhanced digital capabilities and the ability of context-awareness. The cyber-physical objects are embedded in the process models in order to support tracking activities and facilitate process monitoring and control close to real-time.","PeriodicalId":145780,"journal":{"name":"2017 Winter Simulation Conference (WSC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115420720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}