An Extended Deterministic Dendritic Cell Algorithm for Dynamic Job Shop Scheduling

Conference paper


The problem of job shop scheduling in a dynamic environment where random perturbation exists in the system is studied. In this paper, an extended deterministic Dendritic Cell Algorithm (dDCA) is proposed to solve such a dynamic Job Shop Scheduling Problem (JSSP) where unexpected events occurred randomly. This algorithm is designed based on dDCA and makes improvements by considering all types of signals and the magnitude of the output values. To evaluate this algorithm, ten benchmark problems are chosen and different kinds of disturbances are injected randomly. The results show that the algorithm performs competitively as it is capable of triggering the rescheduling process optimally with much less run time for deciding the rescheduling action. As such, the proposed algorithm is able to minimize the rescheduling times under the defined objective and to keep the scheduling process stable and efficient.


Artificial Immune System Slack Time Machine Breakdown Dendritic Cell Algorithm Danger Theory 
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Copyright information

© Springer-Verlag London Limited 2011

Authors and Affiliations

  1. 1.Industrial and Manufacturing Systems Engineering DepartmentThe University of Hong KongHong KongP.R. China

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