
SAI method for solving job shop sequencing problem under certain and uncertain environment
By: Srikant Gupta, ather aziz raina, Irfan Ali and Aquil Ahmed
Open Access
|Dec 2017Abstract
In this investigation, we use SAI method (Gupta et al. 2016), for solving sequencing problem when processing time of the machine is certain or uncertain in nature. The procedure adopted for solving the sequencing problems is easiest and involves the minimum numbers of iterations to obtain the sequence of jobs. The uncertainty in data is represented by triangular or trapezoidal fuzzy numbers. Yager’s ranking function approach is used to convert these fuzzy numbers into a crisp at a prescribed value of α. Stepwise SAI method is then used to obtain optimal job sequence for the problem. Further, the result obtained by SAI method is compared with Johnson’s Method. Numerical examples are given to demonstrate the effectiveness of the proposed approach.
DOI: https://doi.org/10.4038/sljastats.v18i3.7911 | Journal eISSN: 2424-6271
Language: English
Page range: 167 - 186
Published on: Dec 31, 2017
Published by: The Institute of Applied Statistics, Sri Lanka
In partnership with: Paradigm Publishing Services
© 2017 Srikant Gupta, ather aziz raina, Irfan Ali, Aquil Ahmed, published by The Institute of Applied Statistics, Sri Lanka
This work is licensed under the Creative Commons License.