Paper Info
Title
An Extended Deterministic Dendritic Cell Algorithm For Dynamic Job Shop Scheduling
Abstract
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.
Year
DOI
Venue
2010
10.1007/978-0-85729-130-1_30
RESEARCH AND DEVELOPMENT IN INTELLIGENT SYSTEMS XXVII: INCORPORATING APPLICATIONS AND INNOVATIONS IN INTELLIGENT SYSTEMS XVIII
Keywords
Field
DocType
process optimization,job shop scheduling
Lottery scheduling,Mathematical optimization,Job shop scheduling,Fair-share scheduling,Computer science,Flow shop scheduling,Two-level scheduling,Least slack time scheduling,Rate-monotonic scheduling,Dynamic priority scheduling
Conference
Citations 
PageRank 
References 
1
0.38
8
Authors
2
Name
Order
Citations
PageRank
X. N. Qiu110.38
Henry Y. K. Lau216431.98