Pub Date : 2016-12-11DOI: 10.1109/WSC.2016.7822392
Lachlan Birdsey
Complex adaptive systems (CAS) exhibit properties beyond complex systems such as self-organization, adaptability and modularity. Designing models of CAS is typically a non-trivial task as many components are made up of sub-components and rely on a large number of complex interactions. Studying features of these models also requires specific work for each system. Moreover, running these models as simulations with a large number of entities requires a large amount of processing power. We propose a language, Complex Adaptive Systems Language (CASL), and a framework to handle these issues. In particular, an extension to CASL that introduces the concept of ‘semantic grouping’ allows for large scale simulations to execute on relatively modest hardware. A component of our framework, the observation module, aims to provide an extensible and expandable set of metrics to study key features of CAS such as aggregation, adaptability, and modularity, while also allowing for more domain-specific techniques.
{"title":"A framework and Language for Complex Adaptive System modeling and simulation","authors":"Lachlan Birdsey","doi":"10.1109/WSC.2016.7822392","DOIUrl":"https://doi.org/10.1109/WSC.2016.7822392","url":null,"abstract":"Complex adaptive systems (CAS) exhibit properties beyond complex systems such as self-organization, adaptability and modularity. Designing models of CAS is typically a non-trivial task as many components are made up of sub-components and rely on a large number of complex interactions. Studying features of these models also requires specific work for each system. Moreover, running these models as simulations with a large number of entities requires a large amount of processing power. We propose a language, Complex Adaptive Systems Language (CASL), and a framework to handle these issues. In particular, an extension to CASL that introduces the concept of ‘semantic grouping’ allows for large scale simulations to execute on relatively modest hardware. A component of our framework, the observation module, aims to provide an extensible and expandable set of metrics to study key features of CAS such as aggregation, adaptability, and modularity, while also allowing for more domain-specific techniques.","PeriodicalId":367269,"journal":{"name":"2016 Winter Simulation Conference (WSC)","volume":"1048 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123148512","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}
Pub Date : 2016-12-11DOI: 10.1109/WSC.2016.7822155
Wei Li, Ramamurthy Mani, P. Mosterman
A simulation framework is introduced that facilitates hierarchical definition and composition of discrete-event systems. This framework enables modelers to flexibly use graphical block diagrams, state charts, and MATLAB textual object-oriented programming to author custom domain-specific discrete-event systems. The framework has been realized in an implementation that spans multiple software simulation tools including SimEvents, Stateflow, Simulink and MATLAB.
{"title":"Extensible Discrete-Event Simulation framework in SimEvents","authors":"Wei Li, Ramamurthy Mani, P. Mosterman","doi":"10.1109/WSC.2016.7822155","DOIUrl":"https://doi.org/10.1109/WSC.2016.7822155","url":null,"abstract":"A simulation framework is introduced that facilitates hierarchical definition and composition of discrete-event systems. This framework enables modelers to flexibly use graphical block diagrams, state charts, and MATLAB textual object-oriented programming to author custom domain-specific discrete-event systems. The framework has been realized in an implementation that spans multiple software simulation tools including SimEvents, Stateflow, Simulink and MATLAB.","PeriodicalId":367269,"journal":{"name":"2016 Winter Simulation Conference (WSC)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126387563","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}
Pub Date : 2016-12-11DOI: 10.1109/WSC.2016.7822249
William P. Millhiser, Emre A. Veral
We propose a methodology to provide real-time assistance for outpatient scheduling, involving multiple patient types. Schedulers are shown how each prospective placement would impact the day's operational performance for patients and providers. Rooted in prior literature and analytical findings, the information provided to schedulers about vacant slots is based on the probabilities that the calling patient, the already-existing appointments, and the session-end time will be unduly delayed. The information is dynamically updated after every new booking; calculations are driven by historical consultation times and no-show data, and a simulation tool that implements the underlying analytical methodology. Our findings lead to practical guidelines for constructing templates that provide allowances for different service time lengths and variability, no-show rates, and provider-driven performance targets for patient delays and providers' overtime. Extensions to OR scheduling are viable as avoiding session overtime and procedures' completion time delays involve similar considerations.
{"title":"A decision support system for real-time and dynamic scheduling of multiple patient classifications in ambulatory care services","authors":"William P. Millhiser, Emre A. Veral","doi":"10.1109/WSC.2016.7822249","DOIUrl":"https://doi.org/10.1109/WSC.2016.7822249","url":null,"abstract":"We propose a methodology to provide real-time assistance for outpatient scheduling, involving multiple patient types. Schedulers are shown how each prospective placement would impact the day's operational performance for patients and providers. Rooted in prior literature and analytical findings, the information provided to schedulers about vacant slots is based on the probabilities that the calling patient, the already-existing appointments, and the session-end time will be unduly delayed. The information is dynamically updated after every new booking; calculations are driven by historical consultation times and no-show data, and a simulation tool that implements the underlying analytical methodology. Our findings lead to practical guidelines for constructing templates that provide allowances for different service time lengths and variability, no-show rates, and provider-driven performance targets for patient delays and providers' overtime. Extensions to OR scheduling are viable as avoiding session overtime and procedures' completion time delays involve similar considerations.","PeriodicalId":367269,"journal":{"name":"2016 Winter Simulation Conference (WSC)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122224708","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}
Pub Date : 2016-12-11DOI: 10.1109/WSC.2016.7822350
Brittany L. Biagi, N. Fekadu, D. Garbin, S. Gordon, D. Masi
Disasters can cause extraordinary service demand by the public. It is imperative that services supporting disaster response perform with minimal degradation during such events. In order to provide adequate service to special users such as first responders, priority treatment mechanisms have to be developed. Priority treatments have been incorporated for earlier wireless technologies, but have to be established on Long-term Evolution (LTE) / 4G. One of the proposed priority-treatment concepts is Access Class Barring (ACB), which will shed traffic from public users in response to extreme overloads, resulting in priority for special users. However, the degree to which ACB would improve voice call completion is unknown. A discrete-event simulation was performed to model extreme overload situations and predict the performance of ACB under various configurations. The simulation study found that ACB could drastically improve the priority call completion probability in the most extreme overloads while maintaining performance for public traffic.
{"title":"Using simulation to evaluate LTE load control for priority users","authors":"Brittany L. Biagi, N. Fekadu, D. Garbin, S. Gordon, D. Masi","doi":"10.1109/WSC.2016.7822350","DOIUrl":"https://doi.org/10.1109/WSC.2016.7822350","url":null,"abstract":"Disasters can cause extraordinary service demand by the public. It is imperative that services supporting disaster response perform with minimal degradation during such events. In order to provide adequate service to special users such as first responders, priority treatment mechanisms have to be developed. Priority treatments have been incorporated for earlier wireless technologies, but have to be established on Long-term Evolution (LTE) / 4G. One of the proposed priority-treatment concepts is Access Class Barring (ACB), which will shed traffic from public users in response to extreme overloads, resulting in priority for special users. However, the degree to which ACB would improve voice call completion is unknown. A discrete-event simulation was performed to model extreme overload situations and predict the performance of ACB under various configurations. The simulation study found that ACB could drastically improve the priority call completion probability in the most extreme overloads while maintaining performance for public traffic.","PeriodicalId":367269,"journal":{"name":"2016 Winter Simulation Conference (WSC)","volume":"282 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116085295","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}
Pub Date : 2016-12-11DOI: 10.1109/WSC.2016.7822408
Przemysław Szufel, Marcin Czupryna, B. Kamiński
Cloud computing enables massive parallelization of execution of large scale simulation experiments but it is complex to do it in a cost-efficient way. We present methodology used to achieve this goal that was devised in the ROUTE-TO-PA project, where we develop a simulator for generalization of the dynamics of preferences observed on the social platform to the entire population. Experimenting with such a complex simulation model over a computing cluster in the cloud requires solving not only technical challenges (solution architecture and management of dynamically changing infrastructure) but also requires optimization of computing cost. In this work we present our approach (ROUTE-TO-PA SIM) to configure and manage such environment in the Amazon Web Services cloud setting.
云计算使大规模模拟实验的执行大规模并行化，但以一种经济高效的方式实现它是复杂的。我们提出了用于实现ROUTE-TO-PA项目中设计的这一目标的方法，在该项目中，我们开发了一个模拟器，用于将社交平台上观察到的偏好动态推广到整个人群。在云中的计算集群上试验如此复杂的模拟模型不仅需要解决技术挑战(解决方案架构和动态变化基础设施的管理)，还需要优化计算成本。在本文中，我们介绍了在Amazon Web Services云设置中配置和管理这种环境的方法(ROUTE-TO-PA SIM)。
{"title":"Optimal execution of large scale simulations in the cloud. The case of ROUTE-TO-PA SIM online preference simulation","authors":"Przemysław Szufel, Marcin Czupryna, B. Kamiński","doi":"10.1109/WSC.2016.7822408","DOIUrl":"https://doi.org/10.1109/WSC.2016.7822408","url":null,"abstract":"Cloud computing enables massive parallelization of execution of large scale simulation experiments but it is complex to do it in a cost-efficient way. We present methodology used to achieve this goal that was devised in the ROUTE-TO-PA project, where we develop a simulator for generalization of the dynamics of preferences observed on the social platform to the entire population. Experimenting with such a complex simulation model over a computing cluster in the cloud requires solving not only technical challenges (solution architecture and management of dynamically changing infrastructure) but also requires optimization of computing cost. In this work we present our approach (ROUTE-TO-PA SIM) to configure and manage such environment in the Amazon Web Services cloud setting.","PeriodicalId":367269,"journal":{"name":"2016 Winter Simulation Conference (WSC)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115279464","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}
Pub Date : 2016-12-11DOI: 10.1109/WSC.2016.7822134
Mengdi Wang, Ji Liu
Consider the convex optimization problem minx ƒ (g(x)) where both ƒ and g are unknown but can be estimated through sampling. We consider the stochastic compositional gradient descent method (SCGD) that updates based on random function and subgradient evaluations, which are generated by a conditional sampling oracle. We focus on the case where samples are corrupted with Markov noise. Under certain diminishing stepsize assumptions, we prove that the iterate of SCGD converges almost surely to an optimal solution if such a solution exists. Under specific constant stepsize assumptions, we obtain finite-sample error bounds for the averaged iterates of the algorithm. We illustrate an application to online value evaluation in dynamic programming.
{"title":"A stochastic compositional gradient method using Markov samples","authors":"Mengdi Wang, Ji Liu","doi":"10.1109/WSC.2016.7822134","DOIUrl":"https://doi.org/10.1109/WSC.2016.7822134","url":null,"abstract":"Consider the convex optimization problem minx ƒ (g(x)) where both ƒ and g are unknown but can be estimated through sampling. We consider the stochastic compositional gradient descent method (SCGD) that updates based on random function and subgradient evaluations, which are generated by a conditional sampling oracle. We focus on the case where samples are corrupted with Markov noise. Under certain diminishing stepsize assumptions, we prove that the iterate of SCGD converges almost surely to an optimal solution if such a solution exists. Under specific constant stepsize assumptions, we obtain finite-sample error bounds for the averaged iterates of the algorithm. We illustrate an application to online value evaluation in dynamic programming.","PeriodicalId":367269,"journal":{"name":"2016 Winter Simulation Conference (WSC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116694700","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}
Pub Date : 2016-12-11DOI: 10.1109/WSC.2016.7822268
Andreas J. Peirleitner, K. Altendorfer, Thomas Felberbauer
The cost effective management of a supply chain under stochastic influences, e.g. in demand or the replenishment lead time, is a critical issue. In this paper a multi-stage and multi-product supply chain is investigated where each member uses the (s,Q)-policy for inventory management. A bi-objective optimization problem to minimize overall supply chain costs while maximizing service level for retailers is studied. Optimal parameter levels for reorder points and lot sizes are evaluated. In a first step a streamlined analytical solution approach is tested to identify optimal parameter settings. For real applications, this approach neglects the dynamics and interdependencies of the supply chain members. Therefore a simulation-based approach, combining an evolutionary algorithm with simulation, is used for the optimization. The simulation-based approach further enables the modelling of additional real world transportation constraints. The numerical simulation study highlights the potential of simulation-based optimization compared to analytical models for multi-stage multi-product supply chains.
{"title":"A simulation approach for multi-stage supply chain optimization to analyze real world transportation effects","authors":"Andreas J. Peirleitner, K. Altendorfer, Thomas Felberbauer","doi":"10.1109/WSC.2016.7822268","DOIUrl":"https://doi.org/10.1109/WSC.2016.7822268","url":null,"abstract":"The cost effective management of a supply chain under stochastic influences, e.g. in demand or the replenishment lead time, is a critical issue. In this paper a multi-stage and multi-product supply chain is investigated where each member uses the (s,Q)-policy for inventory management. A bi-objective optimization problem to minimize overall supply chain costs while maximizing service level for retailers is studied. Optimal parameter levels for reorder points and lot sizes are evaluated. In a first step a streamlined analytical solution approach is tested to identify optimal parameter settings. For real applications, this approach neglects the dynamics and interdependencies of the supply chain members. Therefore a simulation-based approach, combining an evolutionary algorithm with simulation, is used for the optimization. The simulation-based approach further enables the modelling of additional real world transportation constraints. The numerical simulation study highlights the potential of simulation-based optimization compared to analytical models for multi-stage multi-product supply chains.","PeriodicalId":367269,"journal":{"name":"2016 Winter Simulation Conference (WSC)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124984840","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}
Pub Date : 2016-12-11DOI: 10.1109/WSC.2016.7822281
Fabio Vitor, Vanessa Antunes Santos, L. Chwif
This paper highlights some of the primary concerns about simulation recently raised by academics and practitioners. These concerns influenced the creation of a successful simulation project that improves the check-in at Congonhas Airport in São Paulo, Brazil. Use of simulation was essential in Congonhas because, although significant growth in the number of passengers has occurred over the last decades, Congonhas has limited capacity for expansion due to its location. Two major airlines, which represent 88% of the market share of Congonhas, were considered in this study. Output results demonstrated that a majority of future customers will experience excessive wait times to check in. Therefore, improvement scenarios were proposed in order to meet comfort levels required by international organizations.
{"title":"Warnings about simulation revisited: Improving operations in Congonhas Airport","authors":"Fabio Vitor, Vanessa Antunes Santos, L. Chwif","doi":"10.1109/WSC.2016.7822281","DOIUrl":"https://doi.org/10.1109/WSC.2016.7822281","url":null,"abstract":"This paper highlights some of the primary concerns about simulation recently raised by academics and practitioners. These concerns influenced the creation of a successful simulation project that improves the check-in at Congonhas Airport in São Paulo, Brazil. Use of simulation was essential in Congonhas because, although significant growth in the number of passengers has occurred over the last decades, Congonhas has limited capacity for expansion due to its location. Two major airlines, which represent 88% of the market share of Congonhas, were considered in this study. Output results demonstrated that a majority of future customers will experience excessive wait times to check in. Therefore, improvement scenarios were proposed in order to meet comfort levels required by international organizations.","PeriodicalId":367269,"journal":{"name":"2016 Winter Simulation Conference (WSC)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122623780","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}
Pub Date : 2016-12-11DOI: 10.1109/WSC.2016.7822120
Benjamin G. Thengvall, F. Glover, David F. Davino
Simulation optimization has become commonplace in commercial simulation tools, but automated statistical analysis of the impacts of varying input parameters is much less common. In this paper we explore how both optimization and statistical analysis can be coupled with simulation models to provide key insights for decision makers. A manufacturing example is provided to illustrate the results of multi-objective optimization and post-optimization statistical analysis of the simulation runs. We demonstrate how automated statistical analysis can provide analysts with valuable information on variable sensitivities and good and bad regions of the decision trade space.
{"title":"Coupling optimization and statistical analysis with simulation models","authors":"Benjamin G. Thengvall, F. Glover, David F. Davino","doi":"10.1109/WSC.2016.7822120","DOIUrl":"https://doi.org/10.1109/WSC.2016.7822120","url":null,"abstract":"Simulation optimization has become commonplace in commercial simulation tools, but automated statistical analysis of the impacts of varying input parameters is much less common. In this paper we explore how both optimization and statistical analysis can be coupled with simulation models to provide key insights for decision makers. A manufacturing example is provided to illustrate the results of multi-objective optimization and post-optimization statistical analysis of the simulation runs. We demonstrate how automated statistical analysis can provide analysts with valuable information on variable sensitivities and good and bad regions of the decision trade space.","PeriodicalId":367269,"journal":{"name":"2016 Winter Simulation Conference (WSC)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131469554","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}
Pub Date : 2016-12-11DOI: 10.1109/WSC.2016.7822263
M. Linares, L. Montero, J. Barceló, C. Carmona
Sustainable mobility is not merely a technological question. While automotive technology will be part of the solution, it will also be combined with a paradigm shift from car ownership to vehicle usage, which itself will be facilitated by the application of Information and Communication Technologies that make it possible for a user to have access to a mobility service from anywhere to anywhere at any time. Multiple Passenger Ridesharing and its variants appear to be one of the promising mobility concepts that are emerging. However, in implementing these systems while accounting specifically for time dependencies and time windows that reflect user needs, challenges are raised in terms of real-time fleet dispatching and dynamic route calculation. This paper analyzes and evaluates both aspects through microscopic simulation emulating real-time traffic information while also interacting with a Decision Support System. The paper presents and discusses the obtained results for a Barcelona model.
{"title":"A simulation framework for real-time assessment of dynamic ride sharing demand responsive transportation models","authors":"M. Linares, L. Montero, J. Barceló, C. Carmona","doi":"10.1109/WSC.2016.7822263","DOIUrl":"https://doi.org/10.1109/WSC.2016.7822263","url":null,"abstract":"Sustainable mobility is not merely a technological question. While automotive technology will be part of the solution, it will also be combined with a paradigm shift from car ownership to vehicle usage, which itself will be facilitated by the application of Information and Communication Technologies that make it possible for a user to have access to a mobility service from anywhere to anywhere at any time. Multiple Passenger Ridesharing and its variants appear to be one of the promising mobility concepts that are emerging. However, in implementing these systems while accounting specifically for time dependencies and time windows that reflect user needs, challenges are raised in terms of real-time fleet dispatching and dynamic route calculation. This paper analyzes and evaluates both aspects through microscopic simulation emulating real-time traffic information while also interacting with a Decision Support System. The paper presents and discusses the obtained results for a Barcelona model.","PeriodicalId":367269,"journal":{"name":"2016 Winter Simulation Conference (WSC)","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115142205","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}
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