Online IPA gradient estimators in stochastic continuous fluid models

DOI10.1023/A:1020892306506zbMath1047.90069OpenAlexW91208480WikidataQ62674488 ScholiaQ62674488MaRDI QIDQ1812063

Christos G. Cassandras, Yoraï Wardi, Christos G. Panayiotou, Benjamin Melamed

Publication date: 18 June 2003

Published in: Journal of Optimization Theory and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1023/a:1020892306506

zbMATH Keywords

infinitesimal perturbation analysisStochastic fluid modelsnetwork management and control

Mathematics Subject Classification ID

Sensitivity, stability, parametric optimization (90C31) Management decision making, including multiple objectives (90B50) Deterministic network models in operations research (90B10)

Related Items (11)

Perturbation analysis for production control and optimization of manufacturing systems ⋮ IPA derivatives for a discrete model of make-to-stock production-inventory systems with backorders ⋮ IPA derivatives for Make-to-Stock production-inventory systems with backorders ⋮ Performance optimization of queueing systems with perturbation realization ⋮ Infinitesimal perturbation analysis in networks of stochastic flow models: general framework and case study of tandem networks with flow control ⋮ Perturbation analysis of stochastic fluid models with respect to the fluid arrival process ⋮ Infinitesimal perturbation analysis of a multi-stage tandem of fluid queue with additive loss feedback ⋮ IPA for continuous stochastic marked graphs ⋮ Simulation of IPA gradients in hybrid network systems ⋮ Infinitesimal perturbation analysis of a single-stage fluid queue with loss feedback and non-responsive competing traffic ⋮ IPA derivatives for make-to-stock production-inventory systems with backorders under the (\(\mathbf{R,r}\)) policy

Cites Work

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• Conservation laws and reflection mappings with an application to multiclass mean value analysis for stochastic fluid queues
• On the dynamics and performance of stochastic fluid systems
• Time-driven fluid simulation for high-speed networks
• Perturbation analysis for online control and optimization of stochastic fluid models
• Variational bounds and sensitivity analysis of traffic processes in continuous flow models

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