An Improved Ant Colony Algorithm Based Dynamic Scheduling Method in Job Shop with Parallel Machines

J. Zhang; J.G. Yang; W. Qin; H. Li; Z.G. Xu

doi:10.4028/www.scientific.net/AMR.628.304

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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 628An Improved Ant Colony Algorithm Based Dynamic...

An Improved Ant Colony Algorithm Based Dynamic Scheduling Method in Job Shop with Parallel Machines

Abstract:

In this paper, the authors analysed the impact of machine breakdowns in job shop scheduling problem with parallel machines. A mathematical model with the objective of minimizing the weighted value of makespan and early due date was established. An improved ant colony dynamic scheduling algorithm combined with elite strategy and max-min ant mechanism was designed. Simulation experiments were designed and numerical results verified the superiority of the proposed approach.

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Periodical:

Advanced Materials Research (Volume 628)

Pages:

304-309

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.628.304

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Online since:

December 2012

Authors:

J. Zhang, J.G. Yang, W. Qin, H. Li, Z.G. Xu

Keywords:

Ant Colony Algorithm (ACA), Dynamic Scheduling, Parallel Machines

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References

[1] Jones Albert, Rabelo KuisYih, Yuehwern Y. A hybrid approach for real-time sequencing and scheduling [J]. Int J of Comp Integ Manuf, Vol. 8, Issue 2 (1995), pp.145-154.

Google Scholar

[2] K. J. Chen and P. Ji. A genetic algorithm for dynamic advanced planning and scheduling (DAPS) with afrozen interval [J]. Expert Systems with Applications. Vol. 33, Issue 4 (2006), p.1004–1010

DOI: 10.1016/j.eswa.2006.08.025

Google Scholar