Kriging metamodeling in multiple-objective simulation optimization
نویسندگان
چکیده
This paper describes the application of Kriging metamodeling in multiple-objective simulation optimization. An Arenabased simulation model of an (s, S) inventory system is utilized to demonstrate the capabilities of Kriging metamodeling as a simulation tool. Response surface methodology and Kriging metamodeling are compared to determine the situations in which one approach might be preferred over the other. The optimization approaches described here have the objective of finding the optimal values of reorder point s and maximum inventory level S so as to minimize the total cost of the inventory system while maximizing customer satisfaction. This paper describes two alternative approaches to utilizing Kriging methodology with multiple-objective optimization in simulation studies.
منابع مشابه
Comparative Studies of Metamodeling Techniques Under Multiple Modeling Criteria
Despite advances in computer capacity, the enormous computational cost of running complex engineering simulations makes it impractical to rely exclusively on simulation for the purpose of design optimization. To cut down the cost, surrogate models, also known as metamodels, are constructed from and then used in place of the actual simulation models. In the paper, we systematically compare four ...
متن کاملMetamodeling Method Using Dynamic Kriging for Design Optimization
Metamodeling has been widely used for design optimization by building surrogate models for computationally intensive engineering application problems. Among all the metamodeling methods, the kriging method has gained significant interest for its accuracy.However, in traditional krigingmethods, themean structure is constructed using a fixed set of polynomial basis functions, and the optimization...
متن کاملA Kriging Metamodel Assisted Multi-Objective Genetic Algorithm for Design Optimization
The high computational cost of population based optimization methods, such as multiobjective genetic algorithms (MOGAs), has been preventing applications of these methods to realistic engineering design problems. The main challenge is to devise methods that can significantly reduce the number of simulation (objective/constraint functions) calls. We present a new multi-objective design optimizat...
متن کاملSequential Parameter Optimization in Noisy Environments
Sequential Parameter Optimization is a model-based optimization methodology, which includes several techniques for handling uncertainty. Simple approaches such as sharpening and more sophisticated approaches such as optimal computing budget allocation are available. For many real world engineering problems, the objective function can be evaluated at different levels of fidelity. For instance, a...
متن کاملTaylor Kriging Metamodeling for Simulation Interpolation, Sensitivity Analysis and Optimization Tin-yau Tam Professor Mathematics and Statistics Sensitivity Analysis and Optimization Taylor Kriging Metamodeling for Simulation Interpolation, Sensitivity Analysis and Optimization
Except where reference is made to the work of others, the work described in this dissertation is my own or was done in collaboration with my advisory committee. This dissertation does not include proprietary or classified information. Permission is granted to Auburn University to make copies of this dissertation at its discretion, upon the request of individuals or institutions and at their exp...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Simulation
دوره 87 شماره
صفحات -
تاریخ انتشار 2011