Accelerating the convergence of the stochastic ruler method for discrete stochastic optimization
Proceedings of the 29th conference on Winter simulation
Proceedings of the 31st conference on Winter simulation: Simulation---a bridge to the future - Volume 1
A New Algorithm for Stochastic Discrete Resource AllocationOptimization
Discrete Event Dynamic Systems
Ordinal Comparison via the Nested Partitions Method
Discrete Event Dynamic Systems
Computational Optimization and Applications
Solution of Nonconvex Nonsmooth Stochastic Optimization Problems
Cybernetics and Systems Analysis
Reliability optimization of a complex system by the stochastic branch and bound method
Cybernetics and Systems Analysis
Balanced Explorative and Exploitative Search with Estimation for Simulation Optimization
INFORMS Journal on Computing
A survey on metaheuristics for stochastic combinatorial optimization
Natural Computing: an international journal
Computers and Electronics in Agriculture
A VNS algorithm for noisy problems and its application to project portfolio analysis
SAGA'07 Proceedings of the 4th international conference on Stochastic Algorithms: foundations and applications
Empirical stochastic branch-and-bound for optimization via simulation
Proceedings of the Winter Simulation Conference
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The optimal allocation of indivisible resources is formalized as a stochastic optimization problem involving discrete decision variables. A general stochastic search procedure is proposed, which develops the concept of the branch-and-bound method. The main idea is to process large collections of possible solutions and to devote more attention to the most promising groups. By gathering more information to reduce the uncertainty and by narrowing the search area, the optimal solution can be found with probability one. Special techniques for calculating stochastic lower and upper bounds are discussed. The results are illustrated by a computational experiment.