Some advantages of stochastic methods in multicriteria optimization of multibody systems
type: Item
instance of: scholarly article
title: Some advantages of stochastic methods in multicriteria optimization of multibody systems
zbMATH Open document ID: 0979.74058
author: Peter Eberhard
author: W. Schiehlen
author: D. Bestle
published in: Archive of Applied Mechanics
publication date: 2000-05-09T00:00:00Z
review text: The paper deals with multicriteria optimum design of multibody systems by using the optimization concept based on either a deterministic gradient-based method or a stochastic simulated annealing optimization procedure. The author apply the results to vehicle dynamics, and compare different optimization procedures. It turns out that simulated annealing not only avoids local minima, but also gives a clear picture of Edgeworth-Pareto optimal set and allows to estimate the influence of nonsensitive parameters. Beside the efficiency, these properties have to be considered when one decides whether a stochastic or a deterministic optimization algorithm should be chosen.
reviewed by: Stefan Jendo
Mathematics Subject Classification ID: 74P10
Mathematics Subject Classification ID: 74K99
Mathematics Subject Classification ID: 74H99
Mathematics Subject Classification ID: 70E55
zbMATH DE Number: 1443958
zbMATH Keywords: multicriteria optimum design
zbMATH Keywords: multibody systems
zbMATH Keywords: deterministic gradient-based method
zbMATH Keywords: stochastic simulated annealing optimization
zbMATH Keywords: vehicle dynamics
zbMATH Keywords: Edgeworth-Pareto optimal set
zbMATH Keywords: influence of nonsensitive parameters
Wikidata QID: Q59899898
MaRDI profile type: Publication
full work available at URL: s004190050242
OpenAlex ID: W2047170449
DOI: 10.1007/S004190050242
description: scientific article; zbMATH DE number 1443958