An evaluation of adaptive surrogate modeling based optimization with two benchmark problems
نویسندگان
چکیده
منابع مشابه
An evaluation of adaptive surrogate modeling based optimization with two benchmark problems
Surrogate modeling uses cheap “surrogates” to represent the response surface of simulation models. It involves several steps, including initial sampling, regression and adaptive sampling. This study evaluates an adaptive surrogate modeling based optimization (ASMO) method on two benchmark problems: the Hartman function and calibration of the SAC-SMA hydrologic model. Our results show that: 1) G...
متن کاملEvolutionary Optimization of Computationally Expensive Problems via Surrogate Modeling
We present a parallel evolutionary optimization algorithm that leverages surrogate models for solving computationally expensive design problems with general constraints, on a limited computational budget. The essential backbone of our framework is an evolutionary algorithm coupled with a feasible sequential quadratic programming solver in the spirit of Lamarckian learning.We employ a trust-regi...
متن کاملTwo-layered Surrogate Modeling for Tuning Optimization Metaheuristics
The problem of detecting suitable parameters for metaheuristic optimization algorithms is well known long since. As these nondeterministic methods, e.g. evolution strategies (ES) [1], are highly adaptible to a specific application, detecting good parameter settings is vital for their success. Performance differences of orders of magnitude (in time and/or quality) are often achieved by means of ...
متن کاملA Multiobjective Adaptive Surrogate Modeling-based Optimization (mo-asmo) Framework Using Efficient Sampling Strategies
A novel multiobjective adaptive surrogate modeling-based optimization (MO-ASMO) framework is proposed to utilize a minimal number of training samples efficiently for sequential model updates. All the sample points are enforced to be feasible, and to provide coverage of sparsely explored sparse design regions using a new optimization subproblem. The MO-ASMO method only evaluates high-fidelity fu...
متن کاملan adaptive nonmonotone trust region method for unconstrained optimization problems based on a simple subproblem
using a simple quadratic model in the trust region subproblem, a new adaptive nonmonotone trust region method is proposed for solving unconstrained optimization problems. in our method, based on a slight modification of the proposed approach in (j. optim. theory appl. 158(2):626-635, 2013), a new scalar approximation of the hessian at the current point is provided. our new proposed method is eq...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Environmental Modelling & Software
سال: 2014
ISSN: 1364-8152
DOI: 10.1016/j.envsoft.2014.05.026