Fuzzy scheduling: Modelling flexible constraints vs. coping with incomplete knowledge

An overview of some fuzzy set-based approaches to scheduling is proposed, emphasizing two distinct uses of fuzzy sets: representing preference profiles and modelling uncertainty distributions. The first setting leads to a valued, non-compensatory generalization of constraint-directed scheduling. The...

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Bibliographic Details
Published inEuropean Journal of Operational Research Vol. 147; no. 2; pp. 231 - 252
Main Authors Dubois, Didier, Fargier, Helene, Fortemps, Philippe
Format Book Review Journal Article
LanguageEnglish
Published Amsterdam Elsevier B.V 01.06.2003
Elsevier
Elsevier Sequoia S.A
SeriesEuropean Journal of Operational Research
Subjects
Artificial Intelligence
Computer Science
Constraint propagation
Decision theory
Fuzzy intervals
Fuzzy logic
Fuzzy sets
Mathematical models
Optimization
Possibility theory
Scheduling
Studies
Theory
Uncertainty
Constraint propagation
Fuzzy intervals
Uncertainty
Possibility theory
Scheduling
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Summary:An overview of some fuzzy set-based approaches to scheduling is proposed, emphasizing two distinct uses of fuzzy sets: representing preference profiles and modelling uncertainty distributions. The first setting leads to a valued, non-compensatory generalization of constraint-directed scheduling. The other setting yields a possibility-theoretic counterpart of PERT, where probability distributions of activity durations are changed into possibility distributions, for the purpose of modelling incomplete information. It is pointed out that a special case of the latter, interval-valued PERT, is a difficult, ill-known problem, regarding the determination of critical activities, latest starting times and floats. Lastly when flexible constraints and uncertain processing times are to be jointly considered, the use of possibilistic decision theory leads to the computation of robust schedules.
ISSN:0377-2217
1872-6860
DOI:10.1016/S0377-2217(02)00558-1