A Three-Fold Approach to Solve Dynamic Job Shop Scheduling Problems by Artificial Immune Algorithm

Abstract:

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This paper aims to propose a novel three-fold approach to solve dynamic job-shop scheduling problems by artificial immune algorithm. The proposed approach works in three phases. Firstly, priority rules are deployed to decrease problem scale instead of using scheduling algorithms directly. Secondly, immune algorithm is applied to optimize the individual scheduling modules. Finally, integration schema is employed to reschedule operations and minimize makespan of gross schedule. The integration schema is carried out in a dynamic manner that the previous modules’ machine idle time is searched continuously. In this way, the machine utilization is increased while the objective of makespan minimization is maintained. Efficacy of the proposed approach has been tested with test instances of job-shop scheduling problems. The experimentation results clearly show effectiveness of the proposed approach.

Info:

Periodical:

Advanced Materials Research (Volumes 139-141)

Edited by:

Liangchi Zhang, Chunliang Zhang and Tielin Shi

Pages:

1666-1669

DOI:

10.4028/www.scientific.net/AMR.139-141.1666

Citation:

S. S. Wu et al., "A Three-Fold Approach to Solve Dynamic Job Shop Scheduling Problems by Artificial Immune Algorithm", Advanced Materials Research, Vols. 139-141, pp. 1666-1669, 2010

Online since:

October 2010

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Price:

$35.00

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