A branch and bound method for stochastic global optimization
Copyright policy )A branch and bound method for stochastic global optimization
A stochastic branch and bound method for solving stochastic global optimization problems is proposed. As in the deterministic case, the feasible set is partitioned into compact subsets. To guide the partitioning process the method uses stochastic upper and lower estimates of the optimal value of the objective function in each subset. Convergence of the method is proved and random accuracy estimates derived. Methods for constructing stochastic upper and lower bounds are discussed. The theoretical considerations are illustrated with an example of a facility location problem..
Discrete location and assignment, convergence, stochastic branch-and-bound method, facility location, Branch and bound method, Stochastic programming, Facility location, Global optimization, stochastic global optimization, 510
Discrete location and assignment, convergence, stochastic branch-and-bound method, facility location, Branch and bound method, Stochastic programming, Facility location, Global optimization, stochastic global optimization, 510
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