On-line maintenance job scheduling and assignment to resources in distributed systems by heuristic-based optimization

A heuristic-based optimization algorithm is proposed in this paper for on-line scheduling and assignment of preventive maintenance jobs to processors, to minimize under availability constraints, on a given time-window, the total cost of the maintenance operations of a distributed system. This algori...

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Veröffentlicht in:Journal of intelligent manufacturing 2004-04, Vol.15 (2), p.131-140
Hauptverfasser: Adzakpa, Kossi P., Adjallah, Kondo H., Yalaoui, Farouk
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creator Adzakpa, Kossi P.
Adjallah, Kondo H.
Yalaoui, Farouk
description A heuristic-based optimization algorithm is proposed in this paper for on-line scheduling and assignment of preventive maintenance jobs to processors, to minimize under availability constraints, on a given time-window, the total cost of the maintenance operations of a distributed system. This algorithm minimizes the cost of discharge of preventive maintenance tasks or jobs, while assigning the tasks along with balancing the processors load. It is shown that the problem is NP-hard. To solve it, the concept of job emergency is introduced and the priority rule for total flow time (PRTF) criterion is used in an adapted heuristic job-scheduling model. In addition, the algorithm considers the constraints of precedence among consecutive standby jobs and their emergency. It is depicted the specific properties of the proposed heuristic allowing jobs scheduling in the right order. Computational results illustrate the efficiency of the approach implemented on different system configurations. [PUBLICATION ABSTRACT]
doi_str_mv 10.1023/B:JIMS.0000018029.60981.e6
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subjects Algorithms
Computer Science
Distributed processing
Employment
Flow control
Heuristic
Manufacturing
Operations Research
Optimization
Preventive maintenance
Production scheduling
Queuing theory
Scheduling
Studies
title On-line maintenance job scheduling and assignment to resources in distributed systems by heuristic-based optimization
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