International Journal of Statistics and Applied Mathematics
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International Journal of Statistics and Applied Mathematics

2019, Vol. 4, Issue 5, Part B

Solving flow - shop scheduling problem to minimize total elapsed time using fuzzy approach


Author(s): VS Jadhav and OS Jadhav

Abstract: Job scheduling is concerned with the optimal allocation of scare resources with objective of optimizing one or several criteria. Job scheduling has been a fruitful area of research for many decades in which scheduling resolve both allocation of machines and order of processing. If the jobs are scheduled properly, not only the time is saved but also efficiency of system is increased. In real life situations, the processing times of jobs are not always exact due to incomplete knowledge or an uncertain environment which implies the existence of various external sources and types of uncertainty. Fuzzy set theory can be used to handle uncertainty inherent in actual scheduling problems.
This paper pertains to solving job-shop scheduling problem in fuzzy environment which optimize the total elapsed time. The fuzziness, vagueness or uncertainty in processing time of jobs is presented by triangular fuzzy membership function. Job sequences are constructed with respect to algorithm of average high ranking method and branch and bound technique by fuzzy processing time. A numerical illustration is carried out to the test efficiency of the proposed approaches.


Pages: 130-133 | Views: 221 | Downloads: 8

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How to cite this article:
VS Jadhav, OS Jadhav. Solving flow - shop scheduling problem to minimize total elapsed time using fuzzy approach. Int J Stat Appl Math 2019;4(5):130-133.
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