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Simulation optimization of complex systems with noisy parameter
spaces can become computationally expensive on a single processor
system. This book discusses construction of software for solving
optimization problems by distributing the work load among several
processors residing on a network. Open source repositories are used
for the development of this software. The Simulated Annealing
algorithm is used to search the parameter space for optimization.
Application of the software to stochastic and deterministic problem
scenarios is closely examined. Since the convergence of the
simulated annealing algorithm depends on the choice of annealing
parameters, different types of simple and elaborate cooling
schedules are applied to problem instances and their impact on the
quality of convergence is assessed.
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Loot
Nadine Gordimer
Paperback
 (2)
R383
R318
Discovery Miles 3 180
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