• Jun 20, 2019 News! IJFCC Vol. 6, No. 4-Vol. 7, No. 2 has been indexed by EI (Inspec).   [Click]
  • Jun 26, 2019 News!Vol.8, No.2 has been published with online version.   [Click]
  • Apr 02, 2019 News!The papers published in Vol.7, No.3-No.4 have all received dois from Crossref.
General Information
    • ISSN: 2010-3751 (Print)
    • Frequency: Quarterly
    • DOI: 10.18178/IJFCC
    • Editor-in-Chief: Prof. Mohamed Othman
    • Executive Editor: Ms. Cherry L. Chan
    • Abstracting/ Indexing: Crossref, Electronic Journals LibraryEI (INSPEC, IET), EBSCO, etc.
    • E-mail:  ijfcc@ejournal.net 
Prof. Mohamed Othman
Department of Communication Technology and Network Universiti Putra Malaysia, Malaysia
It is my honor to be the editor-in-chief of IJFCC. The journal publishes good papers in the field of future computer and communication. Hopefully, IJFCC will become a recognized journal among the readers in the filed of future computer and communication.
IJFCC 2014Vol.3(6): 400-404 ISSN: 2010-3751
DOI: 10.7763/IJFCC.2014.V3.336

Bee Colony Optimization Solution to Single Machine Just in Time Scheduling Problem

V. C. Mahavishnu, A. N. Senthilvel, and S. Umamaheswari
Abstract—Objective of this paper is to create optimized Schedule for a set of jobs on a single machine which minimize the total early and tardy penalty. No preemption of jobs is allowed while scheduling. During the process of scheduling, no machine idle time is allowed and the jobs are assumed to be continuously available. This problem of reducing the machine idle time is an NP class problem. The proposed bee schedule algorithm uses the swarm intelligence approach to solve the single machine early/tardy scheduling problem. The solution obtained using the proposed algorithm contains a local selective search procedure to further improve the schedule. This helps to fine tune and achieve more optimal solution to this scheduling problem. The pairwise interchange procedure is also implemented on the schedule obtained in several passes till the range value is obtained, thus attaining the best solution to the problem. The proposed algorithm is tested and found that it outperforms the existing algorithms like dynamic programming and genetic algorithms. Experimental analysis proves that the proposed algorithm is suitable for similar problems also.

Index Terms—Bee schedule algorithm, early/tardy scheduling, NP class problem, single machine scheduling.

The authors are with the Department of Computer Science and Engineering at Coimbatore Institute of Technology, Coimbatore, India (e-mail: mahavishnu.vc@gmail.com, senthilvel.cit.cse@gmail.com, umamaheswari@cit.edu.in).


Cite: V. C. Mahavishnu, A. N. Senthilvel, and S. Umamaheswari, "Bee Colony Optimization Solution to Single Machine Just in Time Scheduling Problem," International Journal of Future Computer and Communication vol. 3, no. 6, pp. 400-404, 2014.

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