Production Planning with Capacitated Resources and Congestion by Hubert Missbauer & Reha Uzsoy

Author:Hubert Missbauer & Reha Uzsoy
Language: eng
Format: epub
ISBN: 9781071603543
Publisher: Springer New York

(6.25)

where J(θ) = Ew[L(θ, w] where Θ denotes the set of all acceptable decision variable vector θ. The decision variables θ can be discrete or continuous. Fu (2002), Henderson and Nelson (2006), and Zapata et al. (2011) provide extensive reviews of this area. A wide variety of such algorithms exist, including genetic algorithms that use the simulation model to compute a fitness measure for different solutions and stochastic approximation methods for continuous state spaces. The latter methods start with an initial solution θ0 that is updated iteratively using an estimate of the gradient ∇J(θ) of J(θ). The general form of the stochastic approximation algorithm is as follows:Step 1: Choose an initial solution θ0. Set n = 0.

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