A branch and bound method for stochastic global optimization
Mathematical Programming: Series A and B
On Optimal Allocation of Indivisibles Under Uncertainty
Operations Research
Nested Partitions Method for Global Optimization
Operations Research
A Stochastic Branch-and-Bound Approach to Activity Crashing in Project Management
INFORMS Journal on Computing
Feature Article: Optimization for simulation: Theory vs. Practice
INFORMS Journal on Computing
A combined procedure for optimization via simulation
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Simulation optimization: a review, new developments, and applications
WSC '05 Proceedings of the 37th conference on Winter simulation
Industrial strength COMPASS: A comprehensive algorithm and software for optimization via simulation
ACM Transactions on Modeling and Computer Simulation (TOMACS)
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We introduce a new method for discrete-decision-variable optimization via simulation that combines the stochastic branch-and-bound method and the nested partitions method in the sense that we take advantage of the partitioning structure of stochastic branch and bound, but estimate the bounds based on the performance of sampled solutions as the nested partitions method does. Our Empirical Stochastic Branch-and-Bound algorithm also uses improvement bounds to guide solution sampling for better performance.