Surrogate-Assisted Artificial Immune Systems for Expensive Optimization Problems
نویسندگان
چکیده
منابع مشابه
INTRODUCTION 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 کاملSurrogate-assisted evolutionary computation: Recent advances and future challenges
Surrogate-assisted, or meta-model based evolutionary computation uses efficient computational models, often known as surrogates or meta-models, for approximating the fitness function in evolutionary algorithms. Research on surrogate-assisted evolutionary computation began over a decade ago and has received considerably increasing interest in recent years. Very interestingly, surrogate-assisted ...
متن کاملOn Constraint Handling in Surrogate-Assisted Evolutionary Many-Objective Optimization
Surrogate-assisted evolutionary multiobjective optimization algorithms are often used to solve computationally expensive problems. But their efficacy on handling constrained optimization problems having more than three objectives has not been widely studied. Particularly the issue of how feasible and infeasible solutions are handled in generating a data set for training a surrogate has not rece...
متن کاملA multi-fidelity surrogate-model-assisted evolutionary algorithm for computationally expensive optimization problems
Integrating data-driven surrogate models and simulation models of di erent accuracies (or delities) in a single algorithm to address computationally expensive global optimization problems has recently attracted considerable attention. However, handling discrepancies between simulation models with multiple delities in global optimization is a major challenge. To address it, the two major contrib...
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 کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2009