A comparison of global optimization algorithms applied to a ride comfort optimization problem

被引:11
作者
Eriksson, P [1 ]
Arora, JS
机构
[1] SCANIA CV AB Buses & Coaches, Structural Dynam R&D, S-64181 Katrineholm, Sweden
[2] Univ Iowa, Ctr Comp Aided Design, Iowa City, IA 52242 USA
关键词
global optimization; ride comfort; finite element; bus; power unit insulation;
D O I
10.1007/s00158-002-0225-z
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This study presents a comparison of global optimization algorithms applied to an industrial engineering optimization problem. Three global stochastic optimization algorithms using continuous variables, i.e. the domain elimination method, the zooming method and controlled random search, have been applied to a previously studied ride comfort optimization problem. Each algorithm is executed three times and the total number of objective function evaluations needed to locate a global optimum is averaged and used as a measure of efficiency. The results show that the zooming method, with a proposed modification, is most efficient in terms of number of objective function evaluations and ability to locate the global optimum. Each design variable is thereafter given a set of discrete values and two optimization algorithms using discrete variables, i.e. a genetic algorithm and simulated annealing, are applied to the discrete ride comfort optimization problem. The results show that the genetic algorithm is more efficient than the simulated annealing algorithm for this particular optimization problem.
引用
收藏
页码:157 / 167
页数:11
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