Grid Computing Model to Solve Job Shop Scheduling and Flow Shop Scheduling by Fuzzy C-Mean Algorithm
Ajendra Kumar1, Preet Pal Singh2, Dipa Sharma3, Pawan Joshi4
1Ajendra Kumar, Department of Mathematics and Statistics, Gurukula Kangri Vishwavidyalaya Haridwar (U.K), India.
2Preet Pal Singh, Department of Mathematics, Pt. L.M.S. (P.G) College, Rishikesh (U.K), India.
3Dipa Sharma, Department of Mathematics, S.D.M. Government (P.G) College, Doiwala (U.K), India.
4Pawan Joshi*, Department of Mathematics and Statistics, Gurukula Kangri Vishwavidyalaya, Haridwar (U.K), India.
Manuscript received on September 23, 2019. | Revised Manuscript received on October 20, 2019. | Manuscript published on October 30, 2019. | PP: 170-179 | Volume-9 Issue-1, October 2019 | Retrieval Number: A1107109119/2019©BEIESP | DOI: 10.35940/ijeat.A1107.109119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This paper presents two computing model in grid environment to utilize the waiting time of a job on particular machines in Job Shop Scheduling and Flow Shop Scheduling for minimize the makespan or total elapsed time. To determine the sequencing of a job we have applied Fuzzy C-Mean (FCM) clustering algorithm in both Job Shop Scheduling problem and Flow Shop Scheduling problem. Flow Shop Scheduling is a classified case of Job Shop Scheduling in which a specific job sequence is pursued strictly. Two illustrative examples of scheduling problems have been solved by this method and compared our results to some other existing methods discussed in the literature. The experimental result shows that the scheduling system using grid computing can allocate the makespan of service jobs effectively and more efficiently.
Keywords: Grid Computing, Job Shop Scheduling, Flow Shop Scheduling, Fuzzy C-Mean Algorithm (FCM).