New strategies for stochastic resource-constrained ...
Document type :
Compte-rendu et recension critique d'ouvrage
Title :
New strategies for stochastic resource-constrained project scheduling
Author(s) :
Rostami, Salim [Auteur]
Creemers, Stefan [Auteur]
Lille économie management - UMR 9221 [LEM]
Leus, Roel [Auteur]
Catholic University of Leuven = Katholieke Universiteit Leuven [KU Leuven]
Creemers, Stefan [Auteur]
Lille économie management - UMR 9221 [LEM]
Leus, Roel [Auteur]
Catholic University of Leuven = Katholieke Universiteit Leuven [KU Leuven]
Journal title :
Journal of Scheduling
Pages :
349–365
Publisher :
Springer Verlag
Publication date :
2017-01-12
ISSN :
1094-6136
HAL domain(s) :
Sciences de l'Homme et Société/Gestion et management
English abstract : [en]
We study the stochastic resource-constrained project scheduling problem or SRCPSP, where project activities have stochastic durations. A solution is a scheduling policy, and we propose a new class of policies that is a ...
Show more >We study the stochastic resource-constrained project scheduling problem or SRCPSP, where project activities have stochastic durations. A solution is a scheduling policy, and we propose a new class of policies that is a generalization of most of the classes described in the literature. A policy in this new class makes a number of a priori decisions in a preprocessing phase, while the remaining scheduling decisions are made online. A two-phase local search algorithm is proposed to optimize within the class. Our computational results show that the algorithm has been efficiently tuned toward finding high-quality solutions and that it outperforms all existing algorithms for large instances. The results also indicate that the optimality gap even within the larger class of elementary policies is very small.Show less >
Show more >We study the stochastic resource-constrained project scheduling problem or SRCPSP, where project activities have stochastic durations. A solution is a scheduling policy, and we propose a new class of policies that is a generalization of most of the classes described in the literature. A policy in this new class makes a number of a priori decisions in a preprocessing phase, while the remaining scheduling decisions are made online. A two-phase local search algorithm is proposed to optimize within the class. Our computational results show that the algorithm has been efficiently tuned toward finding high-quality solutions and that it outperforms all existing algorithms for large instances. The results also indicate that the optimality gap even within the larger class of elementary policies is very small.Show less >
Language :
Anglais
Popular science :
Non
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