A new metamodel-based method for solving semi-expensive simulation optimization problems

被引：5
|
作者：
Moghaddam, Samira [1 ]
Mahlooji, Hashem [1 ]
机构：
[1] Sharif Univ Technol, Dept Ind Engn, Azadi St, Tehran, Iran
来源：
COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION | 2017年 / 46卷 / 06期
关键词：
Kriging; Metamodel-based algorithm; Particle swarm optimization; Semi-expensive simulation problems; Simulation optimization; DESIGN; TIME;
D O I：
10.1080/03610918.2015.1134567
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
In this article, a new algorithm for rather expensive simulation problems is presented, which consists of two phases. In the first phase, as a model-based algorithm, the simulation output is used directly in the optimization stage. In the second phase, the simulation model is replaced by a valid metamodel. In addition, a new optimization algorithm is presented. To evaluate the performance of the proposed algorithm, it is applied to the (s,S) inventory problem as well as to five test functions. Numerical results show that the proposed algorithm leads to better solutions with less computational time than the corresponding metamodel-based algorithm.
引用
收藏
页码：4795 / 4811
页数：17
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