PUBLICATIONS
Profiles
Journal Publications
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Awada, M., Becerik-Gerber, B., Hoque, S., O'Neill, Z., Pedrielli, G., Wen, J. and Wu, T., 2021. Ten questions concerning occupant health in buildings during normal operations and extreme events including the COVID-19 pandemic. Building and Environment, 188, p.107480.
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Mathesen, L., Pedrielli, G., Ng, S.H. and Zabinsky, Z.B., 2021. Stochastic optimization with adaptive restart: A framework for integrated local and global learning. Journal of Global Optimization, 79(1), pp.87-110.
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Kang, Y., Mathesen, L., Pedrielli, G., Ju, F. and Lee, L.H., 2020. Multi-Fidelity Modeling for Analysis and Optimization of Serial Production Lines. IEEE Transactions on Automatic Control.
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Zhao, Q., Zhou, C. and Pedrielli, G., 2020. A Decision Support System for Data-Driven Driver-Experience Augmented Vehicle Routing Problem. Asia-Pacific Journal of Operational Research, 37(05), p.2050018.
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Sun, H., Pedrielli, G., Zhao, G., Zhou, C., Xu, W. and Pan, R., 2020. Cyber coordinated simulation for distributed multi-stage additive manufacturing systems. Journal of Manufacturing Systems, 57, pp.61-71.
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Pedrielli, G., Selcuk Candan, K., Chen, X., Mathesen, L., Inanalouganji, A., Xu, J., Chen, C.H. and Lee, L.H., 2019. Generalized Ordinal Learning Framework (GOLF) for Decision Making with Future Simulated Data. Asia-Pacific Journal of Operational Research, 36(06), p.1940011.
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Liu, Y., Pedrielli, G., Li, H., Lee, L.H., Chen, C.H. and Shortle, J.F., 2019. Optimal Computing Budget Allocation for Stochastic N–k Problem in the Power Grid System. IEEE Transactions on Reliability, 68(3), pp.778-789.
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Pedrielli, G., Xing, Y., Peh, J.H., Koh, K.W. and Ng, S.H., 2019. A real time simulation optimization framework for vessel collision avoidance and the case of singapore strait. IEEE Transactions on Intelligent Transportation Systems, 21(3), pp.1204-1215.
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Zhu, Y., Pedrielli, G. and Hay Lee, L., 2019. TD-OCBA: Optimal computing budget allocation and time dilation for simulation optimization of manufacturing systems. IISE Transactions, 51(3), pp.219-231.
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Pedrielli, G., Matta, A., Alfieri, A. and Zhang, M., 2018. Design and control of manufacturing systems: a discrete event optimization methodology. International Journal of Production Research, 56(1-2), pp.543-564.
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Li, J., Liu, W., Pedrielli, G., Lee, L.H. and Chew, E.P., 2017. Optimal computing budget allocation to select the nondominated systems—A large deviations perspective. IEEE Transactions on Automatic Control, 63(9), pp.2913-2927.
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Pedrielli, G., Hongtao, C., Ng, S.H., Kister, T. and Bressan, S. (2017). A Framework for Real-Time Monitoring of Energy Efficiency of marine vessels. Energy, 145, 246-260.
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Li, H., and Pedrielli, G., 2016. Shipment policy optimisation in a return supply chain for online retailers via stochastic discrete event simulation. International Journal of Simulation and Process Modelling, 11(3-4), pp.241-258.
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Li, H., Pedrielli, G., Lee, L.H., and Chew, E.P., 2017. Enhancement of supply chain resilience through inter-echelon information sharing. Flexible Services and Manufacturing Journal, 29(2), pp.260-285.
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Pedrielli, G., Lee, L. H., and Ng, S. H. (2015). Optimal bunkering contract in a buyer–seller supply chain under price and consumption uncertainty. Transportation Research Part E: Logistics and Transportation Review, 77, 77-94.
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Pedrielli, G., Alfieri, A., and Matta, A., 2015. Integrated simulation–optimisation of pull control systems. International Journal of Production Research, 53(14), pp.4317-4336.
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Alfieri, A., Matta, A., and Pedrielli, G., 2015. Mathematical programming models for joint simulation–optimization applied to closed queueing networks. Annals of Operations Research, 231(1), pp.105-127.
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Pedrielli, G., Sacco, M., Terkaj, W.(10%), Tolio, T. “An HLA-based distributed simulation for networked manufacturing systems analysis”. Journal of Simulation, Vol. 6, Number 4, pp. 237-252. (2012) Operational Research Society Ltd.
Conference Publications (Selected)
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Candelieri, A., Pedrielli, G. 2021. Treed-Gaussian Processes with Support Vector Machines as Nodes for Nonstationary Bayesian Optimization. Conference Submission, Accepted. PDF.
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Pedrielli, G., Huang, H., and Zabinsky, Z.B. 2021. Using Gaussian Processes to Automate Probabilistic Branch & Bound for Global Optimization. Conference Submission, Accepted. PDF.
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Mathesen, L., Pedrielli, G., Fainekos, G. 2021. Efficient Optimization-Based Falsification of Cyber-Physical Systems with Multiple Conjunctive Requirements. Conference Submission. Accepted. PDF.
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Liu, M., Cao, Y., Pedrielli, G. 2021. Partitioning and Gaussian Processes to Accelerate Sampling in Monte Carlo Tree Search for Continuous Decisions. Conference Submission. Accepted. PDF.
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Cao, Y., Thibeault, Q., Chandratre, A., Fainekos, G., and Pedrielli, G. 2021. Part-X: A Family of Stochastic Algorithms for Search-Based Test Generation with Probabilistic Guarantees. Conference Submission. Accepted. PDF
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Xuereb, M., Pedrielli, G., and Ng, S.H. The Stochastic Gaussian Process model averaging for High Dimensional Statistical Learning. 2020. In Proceedings of 2020 Virtual INFORMS Winter Simulation Conference. In Press.
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Carvalhaes, T., Inanlouganji, A., Boyle, E., Jevtič, P., Pedrielli, G. and Reddy, A., 2020, August. A Simulation Framework for Service Loss of Power Networks under Extreme Weather Events: A Case of Puerto Rico. In 2020 IEEE 16th International Conference on Automation Science and Engineering (CASE) (pp. 1532-1537). IEEE.
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Mathesen, L., Li, X., Pedrielli, G., Kandan, K.S. 2019. Global Optimization of High-Dimensional Problems via parallel decomposed Bayesian Optimization. Accepted for Publication 2019 Winter Simulation Conference.
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Zabinsky, Z.B., Pedrielli, G. and Huang, H., 2019, September. A Framework for Multi-fidelity Modeling in Global Optimization Approaches. In International Conference on Machine Learning, Optimization, and Data Science (pp. 335-346). Springer, Cham.
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Tsai, Y.A., Perego, R., Pedrielli, G., Zabinsky, Z.B., Candelieri, A., Huang, H., Mathesen, L. Stochastic Optimization for Feasibility Determination: an Application to Water Pump Operation in Water Distribution Network. Accepted for publication in 2018 INFORMS-WSC Conference, Gethenborg, Sweden.
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Inanlouganji, A., Pedrielli, G., Fainekos, G., Pokutta, S. 2018. Continuous Simulation-Optimization with Model Mismatch Using Gaussian Process Regression. Accepted for publication in 2018 INFORMS-WSC Conference, Gethenborg, Sweden.
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Zhang, M., Matta, A., Alfieri, A., Pedrielli, G. 2018. Simulation-based Benders Cuts: a New Cutting Approach to Approximately Solve Simulation-optimization Problems. Accepted for publication in 2018 INFORMS-WSC Conference, Gethenborg, Sweden.
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Sun, H., Pedrielli, G., Zhao, G., Bragagnolo, A., Zhou, C., Pan, R., Xu, W. 2018. Cyber Coordinated Simulation Models for Multi-Stage Additive Manufacturing of Energy Products. In Proceedings of the 2018 IEEE-CASE Conference, Munich, Germany.
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Pedrielli, G., Ju, F. 2018. Simulation-Predictive Control for Manufacturing Systems. In Proceedings of the 2018 IEEE-CASE Conference, Munich, Germany.
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Mathesen, L., Pedrielli, G., and Ng, S.H. Trust region based stochastic optimization with adaptive restart: A family of global optimization algorithms. In Proceedings of Winter Simulation Conference (WSC), 2017 Winter, pp. 2104-2115. IEEE, 2017.
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Kang, Y., Mathesen, L., Pedrielli, G., Ju, F. 2017. Multi-Fidelity Modeling for Analysis of Serial Production Lines. In Proceedings of the 2017 IEEE-CASE Conference, Xi-An, China. Finalist for best student paper award.
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Zhang, M., Matta, A., and Pedrielli, G. 2017. Simulation-Based Benders’ Cuts generation for the Joint Workstation, Workload and Buffer Allocation Problem. In Proceedings of the 2017 IEEE-CASE Conference, Xi-An, China.
Manuscripts under review
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Ryan, C., Pedrielli, G., Kiatsabaipul, S., Zabinsky, Z.B., Smith, R.L. 2020. Monte-Carlo Fictitious Play. Journal Submission. Under Review. PDF.
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Pedrielli, G., Barton, R.R. 2021. Metamodel-based quantile estimation for tardiness driven control of manufacturing systems. Journal Submission. Under Review. PDF
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Liu, M., Pedrielli, G., Sulc, P., Poppleton, E., Bertsekas, D. 2021. ExpertRNA: A new framework for RNA structure prediction. Journal Submission. Under 2nd Review. PDF (BioRXiv)
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Mathesen, L., Pedrielli, G., Smith, R.L. 2021. Scaling Bayesian Optimization with Game Theory. Journal Submission. Under Review. PDF.