Nash equilibrium solutions in multi-agent project scheduling with milestones - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue European Journal of Operational Research Année : 2021

Nash equilibrium solutions in multi-agent project scheduling with milestones

Résumé

This paper addresses a project scheduling environment in which the activities are partitioned among a set of agents. The project owner is interested in completing the project as soon as possible. Therefore, she/he defines rewards and penalties to stimulate the agents to complete the project faster. The project owner offers a per-day reward for early project completion and defines intermediate project milestones to be met within specific due dates, with associated per-day penalties. Each agent can, therefore, decide the duration of her/his activities, taking into account linear activity crashing costs, the reward for early project completion, and the penalty arising from violating milestone due-dates. We consider Nash equilibria, i.e., situations in which no agent has an interest in individually changing the duration of any of her/his activities, and in particular, the problem of finding a minimum-makespan equilibrium. This problem is known to be NP-hard, and in this paper, we propose a new and efficient exact algorithmic approach for finding the minimum-makespan equilibrium and through an extensive computational campaign we evaluate the role played by milestones in driving the project towards the owner’s goal.
Fichier principal
Vignette du fichier
S0377221721000400.pdf (555.04 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03539307 , version 1 (24-05-2023)

Licence

Paternité - Pas d'utilisation commerciale

Identifiants

Citer

Přemysl Šůcha, Alessandro Agnetis, Marko Šidlovský, Cyril Briand. Nash equilibrium solutions in multi-agent project scheduling with milestones. European Journal of Operational Research, 2021, 294 (1), pp.29-41. ⟨10.1016/j.ejor.2021.01.023⟩. ⟨hal-03539307⟩
35 Consultations
67 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More