Result: Interval analysis in scheduling

Title:
Interval analysis in scheduling
Source:
Principles and practice of constraint programming - CP 2005 (11th international conference, CP 2005, Sitges, Spain, October 1-5, 2005, proceedings)Lecture notes in computer science. :226-240
Publisher Information:
New York, NY: Springer, 2005.
Publication Year:
2005
Physical Description:
print, 15 ref 1
Original Material:
INIST-CNRS
Document Type:
Conference Conference Paper
File Description:
text
Language:
English
Author Affiliations:
IRIT/UPS 118 route de Narbonne, 31062, Toulouse, France
Institute of Mathematics and Computer Science, Wroclaw University of Technology. Wybrzeze Wyspiariskiego 27, 50-370 Wroclaw, Poland
ISSN:
0302-9743
Rights:
Copyright 2006 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.17324937
Database:
PASCAL Archive

Further Information

This paper reconsiders the most basic scheduling problem, that of minimizing the makespan of a partially ordered set of activities, in the context of incomplete knowledge. While this problem is very easy in the deterministic case, its counterpart when durations are interval-valued is much trickier, as standard results and algorithms no longer apply. After positioning this paper in the scope of temporal networks under uncertainty, we provide a complete solution to the problem of finding the latest starting times and floats of activities, and of locating surely critical ones, as they are often isolated. The minimal float problem is NP-hard while the maximal float problem is polynomial. New complexity results and efficient algorithms are provided for the interval-valued makespan minimization problem.