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WSC
2004
13 years 6 months ago
Stochastic Approximation with Simulated Annealing as an Approach to Global Discrete-Event Simulation Optimization
This paper explores an approach to global, stochastic, simulation optimization which combines stochastic approximation (SA) with simulated annealing (SAN). SA directs a search of ...
Matthew H. Jones, K. Preston White
HYBRID
2004
Springer
13 years 10 months ago
Dynamic Partitioning of Large Discrete Event Biological Systems for Hybrid Simulation and Analysis
Abstract. Biological systems involving genetic reactions are large discrete event systems, and often contain certain species that occur in small quantities, and others that occur i...
Natasha A. Neogi
ML
2007
ACM
192views Machine Learning» more  ML 2007»
13 years 4 months ago
Annealing stochastic approximation Monte Carlo algorithm for neural network training
We propose a general-purpose stochastic optimization algorithm, the so-called annealing stochastic approximation Monte Carlo (ASAMC) algorithm, for neural network training. ASAMC c...
Faming Liang
CP
2000
Springer
13 years 9 months ago
Optimal Anytime Constrained Simulated Annealing for Constrained Global Optimization
Abstract. In this paper we propose an optimal anytime version of constrained simulated annealing (CSA) for solving constrained nonlinear programming problems (NLPs). One of the goa...
Benjamin W. Wah, Yixin Chen
WSC
2001
13 years 6 months ago
Hierarchical modeling of a shipyard integrated with an external scheduling application
This paper presents a hierarchical approach on the simulation of large-scale discrete event systems used recently by Kiran Consulting Group (KCG) to model shipyard operations. Bec...
Ali S. Kiran, Tekin Cetinkaya, Juan Cabrera