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Journal Publications
  1. 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.

  2. 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.

  3. Pedrielli, G., Wang, S. and Ng, S.H., 2020. An extended Two-Stage Sequential Optimization approach: Properties and performance. European Journal of Operational Research, 287(3), pp.929-945.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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)
  1. Candelieri, A., Pedrielli, G. 2021. Treed-Gaussian Processes with Support Vector Machines as Nodes for Nonstationary Bayesian Optimization. Conference Submission, Accepted. PDF.

  2. Pedrielli, G., Huang, H., and Zabinsky, Z.B. 2021. Using Gaussian Processes to Automate Probabilistic Branch & Bound for Global Optimization. Conference Submission, Accepted. PDF.

  3. Mathesen, L., Pedrielli, G., Fainekos, G. 2021. Efficient Optimization-Based Falsification of Cyber-Physical Systems with Multiple Conjunctive Requirements. Conference Submission. Accepted. PDF.

  4. 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.

  5. 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. AcceptedPDF

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. Pedrielli, G., Ju, F. 2018. Simulation-Predictive Control for Manufacturing Systems. In Proceedings of the 2018 IEEE-CASE Conference, Munich, Germany.

  15. 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.

  16. 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.

  17. 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
  1. Ryan, C., Pedrielli, G., Kiatsabaipul, S., Zabinsky, Z.B., Smith, R.L. 2020. Monte-Carlo Fictitious Play. Journal Submission. Under Review. PDF.

  2. Pedrielli, G., Barton, R.R. 2021. Metamodel-based quantile estimation for tardiness driven control of manufacturing systems. Journal Submission. Under Review. PDF

  3. 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)

  4. Mathesen, L., Pedrielli, G., Smith, R.L. 2021. Scaling Bayesian Optimization with Game Theory. Journal Submission. Under Review. PDF.

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