DocumentCode :
2962676
Title :
Interests of genetic algorithms to select and optimize scenarios in a system design process
Author :
Baron, Claude ; Esteve, Daniel ; Yacoub, Mohamed
Author_Institution :
LESIA, INSA, Toulouse, France
Volume :
2
fYear :
2004
fDate :
4-7 May 2004
Firstpage :
1453
Abstract :
This paper explores the interest and the possibility to join system design and project management methods and tools. Our motivation is to prevent the obvious incompatibilities between technical objectives and socio-economical requirements in the enterprise. What we recommend is to work on a generic unique model based on the classical top down design steps, to which costs models and non-functional requirements are associated. Project management thus appears as an activity of diagnosis and optimisation, allowing to choose certain realisations between the different possible scenarios and to optimise the management by an allocation of tolerances, which is calculated for each supplier on the base of a global objective. This analysis concludes on the interest of two complementary tools; the evolutionary algorithms to arbitrate the scenarios, and the Monte-Carlo methods for the allocation of tolerances.
Keywords :
Monte Carlo methods; corporate modelling; genetic algorithms; project management; Monte-Carlo methods; enterprise; evolutionary algorithms; genetic algorithms; project management; socio-economical requirements; system design; technical objectives; tolerances allocation; Algorithm design and analysis; Costs; Delay; Design optimization; Environmental economics; Genetic algorithms; Manufacturing; Product design; Project management; Scheduling; evolutionary computing; modeling; project management; selection and optimization techniques; system design;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics, 2004 IEEE International Symposium on
Print_ISBN :
0-7803-8304-4
Type :
conf
DOI :
10.1109/ISIE.2004.1572028
Filename :
1572028
Link To Document :
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