An application of optimization-by-simulation to discrete variable systems
WSC '85 Proceedings of the 17th conference on Winter simulation
Optimization of manufacturing system simulations using perturbation analysis and SENSE
WSC '85 Proceedings of the 17th conference on Winter simulation
`` Direct Search'' Solution of Numerical and Statistical Problems
Journal of the ACM (JACM)
A Simulation Test Approach to the Evaluation of Nonlinear Optimization Algorithms
ACM Transactions on Mathematical Software (TOMS)
Testing Unconstrained Optimization Software
ACM Transactions on Mathematical Software (TOMS)
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There is increasing interest in science and industry in the optimization of computer simulation models. Often these models are not Monte-Carlo simulations, but consist of systems of differential equations, or other mathematical models. These models can present special problems to numerical optimization methods. First, derivatives are often unavailable. Second, function evaluations can be extremely expensive (e.g. 1 hour on an IBM 3090). Third, the numerical accuracy of each function value may depend on a complicated chain of calculations, and so be impractical to pre-specify. This last point makes it difficult to calibrate optimization routines that use finite difference approximations for gradients. This paper presents a strategy for comparing optimization techniques for these problems, and reviews several interesting findings for quasi-Newton methods, simplex search, and others.