Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 30172
A Subjective Scheduler Based on Backpropagation Neural Network for Formulating a Real-life Scheduling Situation

Authors: K. G. Anilkumar, T. Tanprasert

Abstract:

This paper presents a subjective job scheduler based on a 3-layer Backpropagation Neural Network (BPNN) and a greedy alignment procedure in order formulates a real-life situation. The BPNN estimates critical values of jobs based on the given subjective criteria. The scheduler is formulated in such a way that, at each time period, the most critical job is selected from the job queue and is transferred into a single machine before the next periodic job arrives. If the selected job is one of the oldest jobs in the queue and its deadline is less than that of the arrival time of the current job, then there is an update of the deadline of the job is assigned in order to prevent the critical job from its elimination. The proposed satisfiability criteria indicates that the satisfaction of the scheduler with respect to performance of the BPNN, validity of the jobs and the feasibility of the scheduler.

Keywords: Backpropagation algorithm, Critical value, Greedy alignment procedure, Neural network, Subjective criteria, Satisfiability.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1076000

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1132

References:


[1] W. Stinson, "An Introduction to the Design and Analysis of Algorithms", Cambridge University press, 1980, pp.70-103.
[2] T. H. Cormen, C.E. Leiserson, R. L. Rivest and C. Stein, "Introduction to Algorithms," The MIT Press: McGraw-Hill, 2001, pp. 370-399.
[3] K.G Anilkumar and T. Tanprasert, "Neural Network Based Priority Assigner for Job Scheduler", AU Journal of Technology, AU J.T.9 (3) 2006, pp. 181-186.
[4] K.G. Anilkumar and T. Tanprasert, "Neural Network Based Generalized Job-Shop Scheduler," in Proc. 2nd IMT-GT Regional Conference on Mathematics, statistics and Applications, Universiti Sains Malaysia, Penang, Malaysia, 2006, pp. 53 -58.
[5] K.G Anilkumar and T. Tanprasert, "Neural Network Bassed Greedy Job Scheduler," in Proc. National Computer Science and Engineering Conference (NCSEC 2006), Konkhean, Thailand, 2006, pp. 257-262.
[6] K. G. Anilkumar and T. Tanprasert, "Generalized Job-shop Scheduler Using Feed Forward Neural network and Greedy Alignment Procedure," in Proc. IASTED Conference on Artificial Intelligence and Applications, AIA-2007, Innsbruck, Austria, pp. 115-120.
[7] K. G Anilkumar and T. Tanprasert, "A Subjective Scheduler Based on Neural Network for Job Routing in a Generalized Job-Shop Problem", GESTS International Transactions on Computer Science and Engineering, vol.45, 2008, pp. 79-96.
[8] V. B. Rao and H. V. Rao, "Neural Networks & Fuzzy logic," BPB Publications, New Delhi, 1996, pp. 150-300.
[9] R. A. Johnson and D. W. Wichern, "Applied Multivariate Statistical Analysis," 5th edition, NJ: Prentice Hall, NJ, 2002, pp. 668-719.