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Article Dans Une Revue RAIRO - Operations Research Année : 2014

Solving multi-agent scheduling problems on parallel machines with a global objective function

Faiza Sadi
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Ameur Soukhal
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Jean-Charles Billaut

Résumé

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 0, while maintaining the regular objective function of each agent, f k, at a level no greater than a fixed value, εk (fk ∈ {fkmax, ∑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.

Dates et versions

hal-01004026 , version 1 (11-06-2014)

Identifiants

Citer

Faiza Sadi, Ameur Soukhal, Jean-Charles Billaut. Solving multi-agent scheduling problems on parallel machines with a global objective function. RAIRO - Operations Research, 2014, 48 (2), pp.255-269. ⟨10.1051/ro/2014005⟩. ⟨hal-01004026⟩
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