Paper Info
Title
Solving multi-agent scheduling problems on parallel machines with a global objective function.
Abstract
In this study, we consider a scheduling environment with m (m > 1) parallel machines. The set of jobs to schedule is divided into K disjoint subsets. Each subset of jobs is associated with one agent. The K agents compete to perform their jobs on common resources. The objective is to find a schedule that minimizes a global objective function f, while maintaining the regular objective function of each agent, f(k), at a level no greater than a fixed value, epsilon(k) (f(k) E {A., E fk}, k = 0,..., K). This problem is a multi-agent scheduling problem with a global objective function. In this study, we consider the case with preemption and the case without preemption. If preemption is allowed, we propose a polynomial time algorithm based on a network flow approach for the unrelated parallel machine case. If preemption is not allowed, we propose some general complexity results and develop dynamic programming algorithms.
Year
DOI
Venue
2014
10.1051/ro/2014005
RAIRO-OPERATIONS RESEARCH
Keywords
Field
DocType
Scheduling,multi-agent,complexity,dynamic programming
Flow network,Dynamic programming,Mathematical optimization,Preemption,Disjoint sets,Job shop scheduling,Computer science,Scheduling (computing),Time complexity
Journal
Volume
Issue
ISSN
48
2
0399-0559
Citations 
PageRank 
References 
4
0.42
18
Authors
3
Name
Order
Citations
PageRank
F. Sadi140.76
Ameur Soukhal211910.15
Jean-charles Billaut327321.65