Model-Assisted Pattern Search Methods for Optimizing Expensive Computer Simulations
نویسندگان
چکیده
The design and analysis of computer experiments (DACE) usually envisions performing a single experiment, then replacing the expensive simulation with an approximation. When the simulation is a nonlinear function to be optimized, DACE may be inefficient, and sequential strategies that synthesize ideas from DACE and numerical optimization may be warranted. We consider several such strategies within a unified framework in which sequential approximations constructed by kriging are used to accelerate a conventional direct search method. Computational experiments reveal that hybrid strategies outperform both DACE and traditional pattern search.
منابع مشابه
Computer-Assisted Instruction (CAI), Virtual Patients (VP), and Human Patient Simulation (HPS) in Medical Education Based on Gagne’s Educational Design Pattern
Background and objectives: Educational technology is widely used in all parts of medical education. The use and application of common educational technologies and adoption of educational design patterns in medical sciences education can greatly help in medical simulations, training, and improving of clinical skills of nurses and medical students. The aim of this research was to study computer-a...
متن کاملINTRODUCTION AND DEVELOPMENT OF SURROGATE MANAGEMENT FRAMEWORK FOR SOLVING OPTIMIZATION PROBLEMS
In this paper, we have outlined the surrogate management framework for optimization of expensive functions. An initial simple iterative method which we call the “Strawman” method illustrates how surrogates can be incorporated into optimization to stand in for the most expensive function. These ideas are made rigorous by incorporating them into the framework of pattern search methods. The SMF al...
متن کاملA parallel updating scheme for approximating and optimizing high fidelity computer simulations
Approximation methods are often used to construct surrogate models, which can replace expensive computer simulations for the purposes of optimization. One of the most important aspects of such optimization techniques is the choice of model updating strategy. In this paper we employ parallel updates by searching an expected improvement surface generated from a radial basis function model. We loo...
متن کاملA Memetic Algorithm Assisted by an Adaptive Topology RBF Network and Variable Local Models for Expensive Optimization Problems
A common practice in modern engineering is that of simulation-driven optimization. This implies replacing costly and lengthy laboratory experiments with computer experiments, i.e. computationally-intensive simulations which model real world physics with high fidelity. Due to the complexity of such simulations a single simulation run can require up to several hours of CPU time of a high-performa...
متن کاملDiscovering Popular Clicks\' Pattern of Teen Users for Query Recommendation
Search engines are still the most important gates for information search in internet. In this regard, providing the best response in the shortest time possible to the user's request is still desired. Normally, search engines are designed for adults and few policies have been employed considering teen users. Teen users are more biased in clicking the results list than are adult users. This leads...
متن کامل