Complexity analyses for multi-agent scheduling problems with a global agent and equal length jobs

We study the scheduling of independent jobs where several agents compete to perform their jobs on common identical parallel machines: resource manager GA (global agent) wants to minimize a cost function associated with all jobs, while each agent k wants to have another cost function associated with...

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Bibliographic Details
Published inDiscrete optimization Vol. 23; pp. 93 - 104
Main Authors Sadi, F., Soukhal, A.
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.02.2017
Elsevier
Subjects
Algorithms
Complexity
Computer Science
Multi-agent
Operations Research
Parallel machines
Scheduling
Multi-agent
Parallel machines
Scheduling
Algorithms
Complexity
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Summary:We study the scheduling of independent jobs where several agents compete to perform their jobs on common identical parallel machines: resource manager GA (global agent) wants to minimize a cost function associated with all jobs, while each agent k wants to have another cost function associated with its jobs not exceeding a given value Qk, k=1,…,K. The jobs have equal processing requirements. Monotonic regular objective functions depending on the completion times of jobs are considered. The global cost function of agent GA may correspond to the global performance of the workshop independently on the agents objective functions. With various combinations of the objective functions, new complexity results are proposed and polynomial algorithms are derived to find an optimal solution that minimizes the global objective function, subject to the constraints that the objective functions of the other agents do not exceed a given threshold.
ISSN:1572-5286
1873-636X
DOI:10.1016/j.disopt.2017.01.001