Using a standard clock technique for efficient simulation

DOI10.1016/0167-6377(91)90021-GzbMath0745.65095MaRDI QIDQ1183385

Pirooz Vakili

Publication date: 28 June 1992

Published in: Operations Research Letters (Search for Journal in Brave)

zbMATH Keywords

uniformizationrandom variate generationqueuing networksdiscrete-event dynamic systemsefficient simulationstandard clock

Mathematics Subject Classification ID

Probabilistic models, generic numerical methods in probability and statistics (65C20) Applications of Markov renewal processes (reliability, queueing networks, etc.) (60K20) Probabilistic methods, stochastic differential equations (65C99)

Related Items (13)

Universal alignment probabilities and subset selection for ordinal optimization ⋮ Massively parallel SIMD simulation of Markovian DEDS: Event and time synchronous methods ⋮ Parallel simulation of DEDS via event synchronization ⋮ Parallel sample path generation for discrete event systems and the traffic smoothing problem ⋮ Standard clock simulation and ordinal optimization applied to admission control in integrated communication networks ⋮ Uniformization and performance sensitivity estimation in closed queueing networks ⋮ Selecting the best stochastic system for large scale problems in DEDS. ⋮ Ordinal optimization of DEDS ⋮ Optimization via simulation: A review ⋮ Perturbation analysis of discrete event systems: Concepts, algorithms, and applications ⋮ On derivative estimation of single-server queues via structural infinitesimal perturbation analysis ⋮ A simulated annealing applied for optimizing a voice-multihop radio network ⋮ An accelerated stopping rule for the nested partition hybrid algorithm for discrete stochastic optimization

Cites Work

• Unnamed Item
• Discrete-time conversion for simulating semi-Markov processes
• On the efficient generation of discrete event sample paths under different system parameter values
• Comparing Semi-Markov Processes
• Continuity of Generalized Semi-Markov Processes
• Comparing counting processes and queues
• Discrete time methods for simulating continuous time Markov chains
• Uniformization and Hybrid Simulation/Analytic Models of Renewal Processes

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