Can Cui, Teresa Wu, Mengqi Hu, J. Weir, Xianghua Chu
{"title":"Accuracy vs. robustness: Bi-criteria optimized ensemble of metamodels","authors":"Can Cui, Teresa Wu, Mengqi Hu, J. Weir, Xianghua Chu","doi":"10.1109/WSC.2014.7019926","DOIUrl":"https://doi.org/10.1109/WSC.2014.7019926","url":null,"abstract":"Simulation has been widely used in modeling engineering systems. A metamodel is a surrogate model used to approximate a computationally expensive simulation model. Extensive research has investigated the performance of different metamodeling techniques in terms of accuracy and/or robustness and concluded no model outperforms others across diverse problem structures. Motivated by this finding, this research proposes a bi-criteria (accuracy and robustness) optimized ensemble framework to optimally identify the contributions from each metamodel (Kriging, Support Vector Regression and Radial Basis Function), where uncertainties are modeled for evaluating robustness. Twenty-eight functions from the literature are tested. It is observed for most problems, a Pareto Frontier is obtained, while for some problems only a single point is obtained. Seven geometrical and statistical metrics are introduced to explore the relationships between the function properties and the ensemble models. It is concluded that the bi-criteria optimized ensembles render not only accurate but also robust metamodels.","PeriodicalId":446873,"journal":{"name":"Proceedings of the Winter Simulation Conference 2014","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129627488","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":"On a least absolute deviations estimator of a multivariate convex function","authors":"Eunji Lim, Yao Luo","doi":"10.1109/WSC.2014.7020112","DOIUrl":"https://doi.org/10.1109/WSC.2014.7020112","url":null,"abstract":"When estimating a performance measure f* of a complex system from noisy data, the underlying function f* is often known to be convex. In this case, one often uses convexity to better estimate f* by fitting a convex function to data. The traditional way of fitting a convex function to data, which is done by computing a convex function minimizing the sum of squares, takes too long to compute. It also runs into an “out of memory” issue for large-scale datasets. In this paper, we propose a computationally efficient way of fitting a convex function by computing the best fit minimizing the sum of absolute deviations. The proposed least absolute deviations estimator can be computed more efficiently via a linear program than the traditional least squares estimator. We illustrate the efficiency of the proposed estimator through several examples.","PeriodicalId":446873,"journal":{"name":"Proceedings of the Winter Simulation Conference 2014","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128884861","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":"A hybrid simulation framework for integrated management of infrastructure networks","authors":"Mostafa Batouli, A. Mostafavi","doi":"10.1109/WSC.2014.7020166","DOIUrl":"https://doi.org/10.1109/WSC.2014.7020166","url":null,"abstract":"The objective of this paper is to propose and test a framework for integrated assessment of infrastructure systems at the interface between the dynamic behaviors of assets, agencies, and users. For the purpose of this study a hybrid agent-based/mathematical simulation model is created and tested using a numerical example related to a roadway network. The simulation model is then used for investigating multiple performance scenarios pertaining to the road assets at the network level. The results include the simulation and visualization of the impacts of budget constraints on performance of the network over a forty-year policy horizon. Significantly the results highlight the importance of assessing the interactions between infrastructure assets, agencies, and users and demonstrate the capabilities of the proposed modeling framework in capturing the dynamic behaviors and uncertainties pertaining to civil infrastructure management.","PeriodicalId":446873,"journal":{"name":"Proceedings of the Winter Simulation Conference 2014","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130813063","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":"Early detection of bioterrorism: Monitoring disease using an agent-based model","authors":"S. Hu, S. Barnes, B. Golden","doi":"10.1109/WSC.2014.7019898","DOIUrl":"https://doi.org/10.1109/WSC.2014.7019898","url":null,"abstract":"We propose an agent-based model to capture the transmission patterns of diseases caused by bioterrorism attacks or epidemic outbreaks and to differentiate between these two scenarios. Focusing on a region of three cities, we want to detect a bioterrorism attack before a sizeable proportion of the population is infected. Our results indicate that the aggregated infection and death curves in the region can serve as indicators in distinguishing between the two disease scenarios: the slope of the epidemic infection curve will increase initially and decrease afterwards, whereas the slope of the bioterrorism infection curve will strictly decrease. We also conclude that for a bioterrorism outbreak, the bioterrorism source city becomes more dominant as the local working probability pL increases. In contrast, the behavior of individual cities for the epidemic model presents a “time-lag” pattern, especially when pL is large. As pL decreases, the individual city's dynamic curves converge as time progresses.","PeriodicalId":446873,"journal":{"name":"Proceedings of the Winter Simulation Conference 2014","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130935753","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":"Robust rare-event performance analysis with natural non-convex constraints","authors":"J. Blanchet, C. Dolan, H. Lam","doi":"10.1109/WSC.2014.7019924","DOIUrl":"https://doi.org/10.1109/WSC.2014.7019924","url":null,"abstract":"We consider a common type of robust performance analysis that is formulated as maximizing an expectation among all probability models that are within some tolerance of a baseline model in the Kullback-Leibler sense. The solution of such concave program is tractable and provides an upper bound which is robust to model misspecification. However, this robust formulation fails to preserve some natural stochastic structures, such as i.i.d. model assumptions, and as a consequence, the upper bounds might be pessimistic. Unfortunately, the introduction of i.i.d. assumptions as constraints renders the underlying optimization problem very challenging to solve. We illustrate these phenomena in the rare event setting, and propose a large-deviations based approach for solving this challenging problem in an asymptotic sense for a natural class of random walk problems.","PeriodicalId":446873,"journal":{"name":"Proceedings of the Winter Simulation Conference 2014","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130420691","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":"A penalty function approach for simulation optimization with stochastic constraints","authors":"Liujia Hu, S. Andradóttir","doi":"10.1109/WSC.2014.7020201","DOIUrl":"https://doi.org/10.1109/WSC.2014.7020201","url":null,"abstract":"This paper is concerned with continuous simulation optimization problems with stochastic constraints. Thus both the objective function and constraints need to be estimated via simulation. We propose an Adaptive Search with Discarding and Penalization (ASDP) method for solving this problem. ASDP utilizes the penalty function approach from deterministic optimization to convert the original problem into a series of simulation optimization problems without stochastic constraints. We present conditions under which the ASDP algorithm converges almost surely, and conduct numerical studies aimed at assessing its efficiency.","PeriodicalId":446873,"journal":{"name":"Proceedings of the Winter Simulation Conference 2014","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127886761","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":"Immersion, Presence, and Flow in Robot-Aided ISR Simulation-Based Training","authors":"S. Lackey, Crystal S. Maraj, D. Barber","doi":"10.1109/WSC.2014.7020188","DOIUrl":"https://doi.org/10.1109/WSC.2014.7020188","url":null,"abstract":"The Intelligence, Surveillance, and Reconnaissance (ISR) domain offers a rich application environment for Soldier-Robot teaming and involves multiple tasks that can be effectively allocated across human and robot assets based upon their capabilities. The U.S. Armed Forces envisions Robot-Aided ISR (RAISR) as a strategic advantage and decisive force multiplier. Given the rapid advancement of robotics, Human Systems Integration (HSI) represents a critical risk to the success of RAISR. Simulation-Based Training (SBT) will play a key role in mitigating HSI risks and migrating from traditional Soldier-Robot operation to mixed-initiative teaming. However, research is required to understand the SBT methods and tools most applicable to the RAISR task domain. This paper summarizes results from empirical experimentation aimed at comparing traditional SBT strategies (e.g., Massed Exposure, Highlighting), and understanding the impact of Immersion, Presence, and Flow on performance. Relationships between Immersion, Presence, and Flow are explored and recommendations for future research are included.","PeriodicalId":446873,"journal":{"name":"Proceedings of the Winter Simulation Conference 2014","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128835777","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":"Parallel simulation-based optimization on scheduling of a semiconductor manufacturing system","authors":"Yumin Ma, F. Qiao, Wei Yu, Jianfeng Lu","doi":"10.1109/WSC.2014.7020101","DOIUrl":"https://doi.org/10.1109/WSC.2014.7020101","url":null,"abstract":"As an important and challenging problem, the scheduling of semiconductor manufacturing is a hot topic in both engineering and academic fields. Its purpose is to satisfy production constraints on both production process and resources, as well as optimizing some performance indexes like cycle-time, movement, etc. However, due to its complexities, it is hard to describe the scheduling process with a mathematical model, or to use conventional methods to optimize its scheduling problem. A Simulation approach is proposed to optimize the scheduling of a semiconductor manufacturing system, i.e. a simulation-based optimization (SBO) approach. Because the high computational cost of SBO approach could hinder its application in the real production line, a parallel/distributed architecture is discussed to improve its efficiency. Using genetic algorithm (GA) as an optimization algorithm, the proposed parallel-SBO based scheduling approach for semiconductor manufacturing system is tested for its feasibility and effectiveness.","PeriodicalId":446873,"journal":{"name":"Proceedings of the Winter Simulation Conference 2014","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126854387","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}
N. Mustafee, Korina Katsaliaki, Simon J. E. Taylor
{"title":"A review of literature in distributed supply chain simulation","authors":"N. Mustafee, Korina Katsaliaki, Simon J. E. Taylor","doi":"10.1109/WSC.2014.7020128","DOIUrl":"https://doi.org/10.1109/WSC.2014.7020128","url":null,"abstract":"M&S is a decision support technique that enables stakeholders to make better and more informed decisions; application of this to supply chains is referred to as supply chain simulation. The increasingly interconnected enterprise of the digital age benefit from cooperative decision making through the utilization of existing technological foundations, standards and tools (e.g., computer networks, data sharing standards, tools for collaborative working). Distributed Supply Chain Simulation (DSCS) facilitates such collective decision making by enabling simulation models of individual business processes/organizations to execute cooperatively over a computer network. The aim of this research is to identifying the advances in DSCS and its present state of play. Towards realization of this aim we present a methodological review of literature and complement this with our domain-specific knowledge in supply chains and parallel and distributed simulation.","PeriodicalId":446873,"journal":{"name":"Proceedings of the Winter Simulation Conference 2014","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123069918","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}
E. Davis, Christopher D. Johnson, D. J. Levin, Rachel C. Morowitz, D. K. Peterson, Michael R. Pouy, V. Volovoi
{"title":"Aligning wildfire management resourcing decisions with operational needs","authors":"E. Davis, Christopher D. Johnson, D. J. Levin, Rachel C. Morowitz, D. K. Peterson, Michael R. Pouy, V. Volovoi","doi":"10.1109/WSC.2014.7020002","DOIUrl":"https://doi.org/10.1109/WSC.2014.7020002","url":null,"abstract":"A hierarchical modeling and simulation (M&S) framework can help federal agencies integrate the myriad business resourcing decisions they face as unmanned aerospace vehicle (UAV) systems are deployed within their federally authorized charters. An integrated M&S method offers a pragmatic approach to leveraging the power of analytical techniques and coping with the complex support requirements of modern macrosystems. In this paper, we demonstrate the benefits of incorporating several agent-based modeling (ABM) enhancements for UAV route planning into a hierarchical M&S structure.","PeriodicalId":446873,"journal":{"name":"Proceedings of the Winter Simulation Conference 2014","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116106258","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}