Minimizing the expected makespan of a ...
Type de document :
Compte-rendu et recension critique d'ouvrage
Titre :
Minimizing the expected makespan of a project with stochastic activity durations under resource constraints
Auteur(s) :
Titre de la revue :
Journal of Scheduling
Pagination :
263-273
Éditeur :
Springer Verlag
Date de publication :
2015-06-10
ISSN :
1094-6136
Discipline(s) HAL :
Sciences de l'Homme et Société/Gestion et management
Résumé en anglais : [en]
The resource-constrained project scheduling problem (RCPSP) has been widely studied. A fundamental assumption of the basic type of RCPSP is that activity durations are deterministic (i.e., they are known in advance). In ...
Lire la suite >The resource-constrained project scheduling problem (RCPSP) has been widely studied. A fundamental assumption of the basic type of RCPSP is that activity durations are deterministic (i.e., they are known in advance). In reality, however, this is almost never the case. In this article, we illustrate why it is important to incorporate activity duration uncertainty, and develop an exact procedure to optimally solve the stochastic resource-constrained scheduling problem. A computational experiment shows that our approach works best when solving small- to medium-sized problem instances where activity durations have a moderate-to-high level of variability. For this setting, our model outperforms the existing state-of-the-art. In addition, we use our model to assess the optimality gap of existing heuristic approaches, and investigate the impact of making scheduling decisions also during the execution of an activity rather than only at the end of an activity.Lire moins >
Lire la suite >The resource-constrained project scheduling problem (RCPSP) has been widely studied. A fundamental assumption of the basic type of RCPSP is that activity durations are deterministic (i.e., they are known in advance). In reality, however, this is almost never the case. In this article, we illustrate why it is important to incorporate activity duration uncertainty, and develop an exact procedure to optimally solve the stochastic resource-constrained scheduling problem. A computational experiment shows that our approach works best when solving small- to medium-sized problem instances where activity durations have a moderate-to-high level of variability. For this setting, our model outperforms the existing state-of-the-art. In addition, we use our model to assess the optimality gap of existing heuristic approaches, and investigate the impact of making scheduling decisions also during the execution of an activity rather than only at the end of an activity.Lire moins >
Langue :
Anglais
Vulgarisation :
Non
Collections :
Source :
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