Job Scheduling System using Fuzzy Logic Approach

International Journal of Computer Trends and Technology (IJCTT)          
© 2016 by IJCTT Journal
Volume-42 Number-2
Year of Publication : 2016
Authors : Odii J. N, Onwuama T.U, Okpalla C.L, Ejem A


Odii J. N, Onwuama T.U, Okpalla C.L, Ejem A  "Job Scheduling System using Fuzzy Logic Approach". International Journal of Computer Trends and Technology (IJCTT) V42(2):77-85, December 2016. ISSN:2231-2803. Published by Seventh Sense Research Group.

Abstract -
Job scheduling system using fuzzy logic is a new approach to job scheduling developed to achieve a near optimal schedule in small scale establishments. In recent times, a lot of confusion abounds in a work environment when multiple jobs are on queue waiting to be processed. It becomes imperative to develop a system that is capable of providing a means of scheduling jobs in a workshop. Our work therefore intends to develop a system for users that have little or no knowledge of mathematical models and other approaches towards scheduling of jobs. Structured System Analysis and Design Methodology (SSADM) was deployed as the research methodology while java programming language was used and Microsoft access was deployed for the database. A fuzzy rule based application developed in this research can be integrated into any system and has the capacity to efficiently schedule jobs so as to reduce time of delivery.

[1] E. Cox, (1993): “Adaptive Fuzzy Systems”, IEEE Spectrum, p27-31
[2] M.M. Gupta and Y. Tsukamoto (1980): “Fuzzy Logic Controllers: A perspective”, proceedings of the Joint Automatic Control conference, San Francisco. P FA10-C
[3] B. Kosko (1992):” Neural Networks and Fuzzy Systems: A Dynamic Systems Approach to machine Intelligence”, Prentice hall, Englewood Cliffs, New Jersey.
[4] C.C. Lee (1990): “Fuzzy Logic in Control Systems”: Fuzzy logic controller-1, 11.IEEE Transactions on Systems. Man and cybernetics, Vol 20 no.2.p 404-432.
[5] H.R. Lemke and W.J.M. Kickert (1976) “The applications of Fuzzy set theory to control a warm water process”.
[6] E.H. Mamdani and S. Assilian (1975): “An experiment in Linguistic Synthesis with a fuzzy logic controller”, International Journal of Man machine studies, vol 7 p1-13.
[7] D. McNeill and P. Freiberger (1993): “Fuzzy Logic”, Simon and Schuster, New York.
[8] J.J. Ostergaard,(1976): “Fuzzy logic Control of a heat exchanger process”. No 7601, electric power Engineering Dept, Technical University of Denmark, Lyngby.
[9] D.G .Schwartz and G.J. Klir (1992): “Fuzzy Logic Flowers in Japan”, IEEE Spectrum, p 32-35
[10] R. Wiggins (1992): Docking a Truck:” Fuzzy, AI Expert”. P28-35.
[11] O. Yagishita, O. Itoh and M. Sugeno (1985): “Application of Fuzzy Reasoning to the water Purification Process”. Industrial Application Fuzzy Control M. Sugeno (Ed), P. 19-40.
[12] S. Yasunobu, S. Miyamoto and H. Ihara (1985): “Automatic Train Operations by Predictive Fuzzy Control, Industrial Applications of Fuzzy control,” M. Sugeno (Ed), P1-18.
[13] L.A. Zadeh (1985): “Fuzzy sets, Usuality and Common Sense Reasoning”, EECS Technical Report, University of California, Berkeley.
[14] D.A. Rutherford (1976): “The Implementation and Evaluation of Fuzzy control algorithm for a sinter plant”. EES-MMS-DSFR-76, Queen Mary College University London (Workshop Proceedings).

Job, Fuzzy Logic, Optimization, Model, Rule.