Discrete optimization via simulation using COMPASS. We propose an optimization-via-simulation algorithm, called COMPASS, for use when the performance measure is estimated via a stochastic, discrete-event simulation, and the decision variables are integer ordered. We prove that COMPASS converges to the set of local optimal solutions with probability 1 for both terminating and steady-state simulation, and for both fully constrained problems and partially constrained or unconstrained problems under mild conditions

References in zbMATH (referenced in 34 articles , 1 standard article )

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  1. He, Xinyu; Reyes, Kristofer G.; Powell, Warren B.: Optimal learning with local nonlinear parametric models over continuous designs (2020)
  2. Powell, Warren B.: A unified framework for stochastic optimization (2019)
  3. Zhang, Qi; Hu, Jiaqiao: Simulation optimization using multi-time-scale adaptive random search (2019)
  4. Mao, Jianfeng; Cassandras, Christos G.: Solving a class of simulation-based optimization problems using “optimality in probability” (2018)
  5. Fleck, Julia L.; Cassandras, Christos G.: Optimal design of personalized prostate cancer therapy using infinitesimal perturbation analysis (2017)
  6. Horng, Shih-Cheng; Lin, Shieh-Shing: Ordinal optimization based metaheuristic algorithm for optimal inventory policy of assemble-to-order systems (2017)
  7. Wang, Honggang: Multi-objective retrospective optimization using stochastic zigzag search (2017)
  8. Amaran, Satyajith; Sahinidis, Nikolaos V.; Sharda, Bikram; Bury, Scott J.: Simulation optimization: a review of algorithms and applications (2016)
  9. Xie, Jing; Frazier, Peter I.; Chick, Stephen E.: Bayesian optimization via simulation with pairwise sampling and correlated prior beliefs (2016)
  10. Alfieri, Arianna; Matta, Andrea; Pedrielli, Giulia: Mathematical programming models for joint simulation-optimization applied to closed queueing networks (2015)
  11. Berkhout, Joost: An accelerated stopping rule for the nested partition hybrid algorithm for discrete stochastic optimization (2015)
  12. Tsai, Shing Chih; Liu, Chung Hung: A simulation-based decision support system for a multi-echelon inventory problem with service level constraints (2015)
  13. Xia, Li; Jia, Qing-Shan: Parameterized Markov decision process and its application to service rate control (2015)
  14. Amaran, Satyajith; Sahinidis, Nikolaos V.; Sharda, Bikram; Bury, Scott J.: Simulation optimization: a review of algorithms and applications (2014)
  15. Tsai, Shing Chih; Fu, Sheng Yang: Genetic-algorithm-based simulation optimization considering a single stochastic constraint (2014)
  16. Xu, Jie; Vidyashankar, Anand; Nielsen, Martin K.: Drug resistance or re-emergence? Simulating equine parasites (2014)
  17. Ahmed, Shamsuddin: Performance of derivative free search ANN training algorithm with time series and classification problems (2013)
  18. Alfieri, Arianna; Matta, Andrea: Mathematical programming formulations for approximate simulation of multistage production systems (2012)
  19. Wang, Honggang: Retrospective optimization of mixed-integer stochastic systems using dynamic simplex linear interpolation (2012)
  20. Yang, Feng; Liu, Jingang: Simulation-based transfer function modeling for transient analysis of general queueing systems (2012)

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