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ILP and CP Formulations for the Lazy Bureaucrat Problem

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Date
2015
Notes
LNCS, Vol. 9075
Dewey
Recherche opérationnelle
Sujet
combinatorial optimization
JEL code
C61; C44
DOI
http://dx.doi.org/10.1007/978-3-319-18008-3_18
Book title
Integration of AI and OR Techniques in Constraint Programming 12th International Conference, CPAIOR 2015, Barcelona, Spain, May 18-22, 2015, Proceedings
Author
Laurent Michel
Publisher
Springer
Publisher city
Berlin Heidelberg
Year
2015
ISBN
978-3-319-18007-6; 978-3-319-18008-3
Book URL
10.1007/978-3-319-18008-3
URI
https://basepub.dauphine.fr/handle/123456789/16411
Collections
  • LAMSADE : Publications
Metadata
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Author
Furini, Fabio
989 Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Ljubić, Ivana
Sinnl, Markus
Type
Communication / Conférence
Item number of pages
255-270
Abstract (EN)
Lazy reformulations of classical combinatorial optimization problems are new and challenging classes of problems. In this paper we focus on the Lazy Bureaucrat Problem (LBP) which is the lazy counterpart of the knapsack problem. Given a set of tasks with a common arrival time and deadline, the goal of a lazy bureaucrat is to schedule a least profitable subset of tasks, while having an excuse that no other tasks can be scheduled without exceeding the deadline.Three ILP formulations and their CP counterparts are studied and implemented. In addition, a dynamic programming algorithm that runs is pseudo-polynomial time and polynomial greedy heuristics are implemented and computationally compared with ILP/CP approaches. For the computational study, a large set of knapsack-type instances with various characteristics is used to examine the applicability and strength of the proposed approaches.

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