{"title":"An Automated Framework for Generating Synthetic Point Clouds from as-Built BIM with Semantic Annotation for Scan-to-BIM","authors":"J. Ma, Bing Han, Fernanda Leite","doi":"10.1109/WSC52266.2021.9715301","DOIUrl":"https://doi.org/10.1109/WSC52266.2021.9715301","url":null,"abstract":"Data scarcity is a major constraint which hinders Scan-to-BIM's generalizability in unseen environments. Manual data collection is not only time-consuming and laborious but especially achieving the 3D point clouds is in general very limited due to indoor environment characteristics. In addition, ground-truth information needs to be attached for the effective utilization of the achieved dataset which also requires considerable time and effort. To resolve these issues, this paper presents an automated framework which integrates the process of generating synthetic point clouds and semantic annotation from as-built BIMs. A procedure is demonstrated using commercially available software systems. The viability of the synthetic point clouds is investigated using a deep learning semantic segmentation algorithm by comparing its performance with real-world point clouds. Our proposed framework can potentially provide an opportunity to replace real-world data collection through the transformation of existing as-built BIMs into synthetic 3D point clouds.","PeriodicalId":369368,"journal":{"name":"2021 Winter Simulation Conference (WSC)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115132169","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":"Explainable Modeling in Digital Twin","authors":"Lu Wang, Tianhu Deng, Zeyu Zheng, Z. Shen","doi":"10.1109/WSC52266.2021.9715321","DOIUrl":"https://doi.org/10.1109/WSC52266.2021.9715321","url":null,"abstract":"Stakeholders' participation in the modeling process is important to successful Digital Twin (DT) implementation. The key question in the modeling process is to decide which options to include. Explaining the key question clearly ensures the organizations and end-users know what the digital models in DT are capable of. To support successful DT implementation, we propose a framework of explainable modeling to enable the collaboration and interaction between modelers and stakeholders. We formulate the modeling process mathematically and develop three types of automatically generated explanations to support understanding and build trust. We introduce three explainability scores to measure the value of explainable modeling. We illustrate how the proposed explainable modeling works by a case study on developing and implementing a DT factory. The explainable modeling increases communication efficiency and builds trust by clearly expressing the model competencies, answering key questions in modeling automatically, and enabling consistent understanding of the model.","PeriodicalId":369368,"journal":{"name":"2021 Winter Simulation Conference (WSC)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121803427","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}
Yijie Peng, M. Fu, Jiaqiao Hu, P. L'Ecuyer, B. Tuffin
{"title":"Variance Reduction for Generalized Likelihood Ratio Method in Quantile Sensitivity Estimation","authors":"Yijie Peng, M. Fu, Jiaqiao Hu, P. L'Ecuyer, B. Tuffin","doi":"10.1109/WSC52266.2021.9715488","DOIUrl":"https://doi.org/10.1109/WSC52266.2021.9715488","url":null,"abstract":"We apply the generalized likelihood ratio (GLR) methods in Peng et al. (2018) and Peng et al. (2021) to estimate quantile sensitivities. Conditional Monte Carlo and randomized quasi-Monte Carlo methods are used to reduce the variance of the GLR estimators. The proposed methods are applied to a toy example and a stochastic activity network example. Numerical results show that the variance reduction is significant.","PeriodicalId":369368,"journal":{"name":"2021 Winter Simulation Conference (WSC)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117163193","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 Societies in the Anthropocene: Challenges and Opportunities for Modeling Climate, Conflict, and Cooperation","authors":"F. Shults, W. Wildman, M. Toft, Antje Danielson","doi":"10.1109/WSC52266.2021.9715391","DOIUrl":"https://doi.org/10.1109/WSC52266.2021.9715391","url":null,"abstract":"Computational approaches to climate modeling have advanced rapidly in recent years, as have the tools and techniques associated with the construction of artificial life, artificial societies, and social simulation experiments. However, the use of computer simulation to study the effects of climate change on human conflict and cooperation is still relatively rare. In this article, we consider some of the challenges and opportunities that face interdisciplinary teams seeking to develop models that incorporate human, ecological, and natural systems. There is an urgency to this task because climate-abetted socio-economic and inter-cultural stress can trigger conflict at all scales, which exacerbates human suffering. We argue that the interdisciplinary community of scholars with expertise in multi-agent artificial intelligence simulation and artificial life modeling have a unique opportunity to collaborate and address these challenges by attempting to develop artificial societies capable of uncovering adaptive pathways that can minimize social conflict and maximize cooperation in the face of climate-abetted social and ecological change.","PeriodicalId":369368,"journal":{"name":"2021 Winter Simulation Conference (WSC)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120900392","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":"Comparing the Effect of Code Optimizations on Simulation Runtime Across Synchronous Cellular Automata Models of HIV","authors":"Junjiang Li, P. Giabbanelli, Till Köster","doi":"10.1109/WSC52266.2021.9715453","DOIUrl":"https://doi.org/10.1109/WSC52266.2021.9715453","url":null,"abstract":"Models developed by domain experts occasionally struggle to achieve a sufficient execution speed. Improving performances requires expertise in parallel and distributed simulations, hardware, or time to profile performances to identify bottlenecks. However, end-users in biological simulations of the Human Immunodeficiency Virus (HIV) have repeatedly demonstrated that these resources are either not available or not sought, resulting in models that are developed through user-friendly languages and platforms, then used on workstations. This situation becomes problematic when performances cannot cope with the salient characteristics of the phenomenon that is modeled, as is the case with cellular automata (CA) models of HIV. In this paper, we optimize the Python code of CA models of HIV to scale the number of cells handled by a simulation on a workstation commonly available to end-users. We demonstrate this scalability via five HIV CA models and compare these results to assess how modeling choices can impact runtime.","PeriodicalId":369368,"journal":{"name":"2021 Winter Simulation Conference (WSC)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124840022","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 Modelling Of Repairable Fault Trees From Time Series Data With Missing Information","authors":"P. Niloofar, S. Lazarova-Molnar","doi":"10.1109/WSC52266.2021.9715375","DOIUrl":"https://doi.org/10.1109/WSC52266.2021.9715375","url":null,"abstract":"Fault tree analysis is one of the most popular techniques for dependability analysis of a wide range of systems. True fault-related behavior of a system would be more accurately reflected if the system's fault tree is derived from a combination of observational data and expert knowledge, rather than expert knowledge alone. The concept of learning fault trees from data becomes more significant when systems change their behaviors during their lifetimes. We present an algorithm for learning fault trees of systems with missing information on fault occurrences of basic events. This algorithm extracts repairable fault trees from incomplete multinomial time series data, and then uses simulation to estimate the system's reliability measures. Our algorithm is not limited to exponential distributions or binary events. Furthermore, we assess the sensitivity of our algorithm to different percentages of missingness and amounts of available data.","PeriodicalId":369368,"journal":{"name":"2021 Winter Simulation Conference (WSC)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123582441","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":"From Logistics Process Models to Automated Integration Testing: Proof-of-Concept Using Open-Source Simulation Software","authors":"Paul Reichardt, W. Hofmann, T. Reggelin, S. Lang","doi":"10.1109/WSC52266.2021.9715310","DOIUrl":"https://doi.org/10.1109/WSC52266.2021.9715310","url":null,"abstract":"This paper explores the practical integration of simulation methods into software development processes. An automated integration testing approach is presented, which enables continuous virtual commissioning. For this purpose, an analysis of the current state of knowledge and the standards of software development is presented. This is followed by a case study on logistics order management, referring to a typical B2B application in the retail logistics sector. The proof-of-concept shows how the usage of a simulation model for automated integration testing and its inclusion into continuous-integration can help to ensure software quality, particularly for process-centered logistics applications. The implemented setup proves the feasibility of the approach, using standard open-source development tools, and a Python-based open-source simulation library.","PeriodicalId":369368,"journal":{"name":"2021 Winter Simulation Conference (WSC)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126711245","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":"Tutorial: Graphical Methods for the Design and Analysis of Experiments","authors":"R. Barton","doi":"10.1109/WSC52266.2021.9715394","DOIUrl":"https://doi.org/10.1109/WSC52266.2021.9715394","url":null,"abstract":"You have built a simulation model, but now must choose runs to i) validate it, and ii) to gain insight about the associated real system and to make managerial recommendations. Do you need guidance? This introductory tutorial views the design of experiments as a five-step process, and presents graphical tools for each of the five steps. Further, with a graphical framework for the design, results can be presented graphically as well, helping you communicate the results visually to management in a way that builds trust.","PeriodicalId":369368,"journal":{"name":"2021 Winter Simulation Conference (WSC)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126933168","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}
L. D. C. Martins, A. Juan, Maria Torres, E. Pérez-Bernabeu, C. G. Corlu, J. Faulin
{"title":"Solving an Urban Ridesharing Problem with Stochastic Travel Times: A Simheuristic Approach","authors":"L. D. C. Martins, A. Juan, Maria Torres, E. Pérez-Bernabeu, C. G. Corlu, J. Faulin","doi":"10.1109/WSC52266.2021.9715370","DOIUrl":"https://doi.org/10.1109/WSC52266.2021.9715370","url":null,"abstract":"Ridesharing and carsharing concepts are redefining mobility practices in cities across the world. These concepts, however, also raise noticeable operational challenges that need to be efficiently addressed. In the urban ridesharing problem (URSP), a fleet of small private vehicles owned by citizens should be coordinated in order to pick up passengers on their way to work, hence maximizing the total value of their trips while not exceeding a deadline for reaching the destination points. Since this is a complex optimization problem, most of the existing literature assumes deterministic travel times. This assumption is unrealistic and, for this reason, we discuss a richer URSP variant in which travel times are modeled as random variables. Using random travel times also forces us to consider a probabilistic constraint regarding the duration of each trip. For solving this stochastic optimization problem, a simheuristic approach is proposed and tested via a series of computational experiments.","PeriodicalId":369368,"journal":{"name":"2021 Winter Simulation Conference (WSC)","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122571455","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}
S. Hoops, Jiangzhuo Chen, Abhijin Adiga, B. Lewis, H. Mortveit, Hannah Baek, M. Wilson, D. Xie, S. Swarup, S. Venkatramanan, Justin Crow, Elena Diskin, S. Levine, Helen Tazelaar, Brooke Rossheim, C. Ghaemmaghami, Rebecca Early, C. Barrett, M. Marathe, C. Price
{"title":"High Performance Agent-Based Modeling to Study Realistic Contact Tracing Protocols","authors":"S. Hoops, Jiangzhuo Chen, Abhijin Adiga, B. Lewis, H. Mortveit, Hannah Baek, M. Wilson, D. Xie, S. Swarup, S. Venkatramanan, Justin Crow, Elena Diskin, S. Levine, Helen Tazelaar, Brooke Rossheim, C. Ghaemmaghami, Rebecca Early, C. Barrett, M. Marathe, C. Price","doi":"10.1109/WSC52266.2021.9715382","DOIUrl":"https://doi.org/10.1109/WSC52266.2021.9715382","url":null,"abstract":"Contact tracing (CT) is an important and effective intervention strategy for controlling an epidemic. Its role becomes critical when pharmaceutical interventions are unavailable. CT is resource intensive, and multiple protocols are possible, therefore the ability to evaluate strategies is important. We describe a high-performance, agent-based simulation model for studying CT during an ongoing pandemic. This work was motivated by the COVID-19 pandemic, however framework and design are generic and can be applied in other settings. This work extends our HPC-oriented ABM framework EpiHiper to efficiently represent contact tracing. The main contributions are: (i) Extension of EpiHiper to represent realistic CT processes. (ii) Realistic case study using the VA network motivated by our collaboration with the Virginia Department of Health.","PeriodicalId":369368,"journal":{"name":"2021 Winter Simulation Conference (WSC)","volume":"230 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114254410","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}