Simulation-based discrete optimization of stochastic discrete event systems subject to non closed form constraints

Jie Li Alexandre Sava 1 Xiolan Xie
1 COSTEAM - Optimal and secure management of manufacturing systems
Inria Nancy - Grand Est, UPVM - Université Paul Verlaine - Metz
Abstract : This technical note addresses the discrete optimization of stochastic discrete event systems for which both the performance function and the constraint function are not known but can be evaluated by simulation and the solution space is either finite or unbounded. Our method is based on random search in a neighborhood structure called the most promising area proposed in [7] and a moving observation area. The simulation budget is allocated dynamically to promising solutions. Simulation-based constraints are taken into account in an augmented performance function via an increasing penalty factor. We prove that under some assumptions, the algorithm converges with probability 1 to a set of true local optimal solutions. These assumptions are restrictive and difficult to verify but we hope that the encouraging numerical results would motivate future research exploiting ideas of this technical note.
Type de document :
Article dans une revue
IEEE Transactions on Automatic Control, Institute of Electrical and Electronics Engineers, 2009, 54 (12), pp.2900-2908. 〈10.1109/TAC.2009.2033847〉
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https://hal.inria.fr/inria-00600372
Contributeur : Ist Inria Nancy Grand Est <>
Soumis le : mardi 14 juin 2011 - 16:28:16
Dernière modification le : mercredi 15 mars 2017 - 12:12:37

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Jie Li, Alexandre Sava, Xiolan Xie. Simulation-based discrete optimization of stochastic discrete event systems subject to non closed form constraints. IEEE Transactions on Automatic Control, Institute of Electrical and Electronics Engineers, 2009, 54 (12), pp.2900-2908. 〈10.1109/TAC.2009.2033847〉. 〈inria-00600372〉

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