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International Journal of Statistika and Mathematika, ISSN: 2277- 2790 E-ISSN: 2249-8605


Volume 3, Issue 1, 2012 pp 01-05


Research Article


Selection of Job Shop Scheduling Problem Using Fuzzy Linguistic Variables.

Vikas S. Jadhav1 and V. H. Bajaj2

{1Research Student, 2Professor} Department of Statistics, Dr.B.A.M.University, Aurangabad-431004(M.S) INDIA.

Academic Editor:  Dr. Dase R.K.



Job-shop scheduling (JSS) is a difficult problem, both theoretically and practically. The theoretical problems stem from the search for optimal schedules to a �Minimum /limited number of resources (Machines)� to complete the �Maximum works (Tasks) with customers satisfaction. This paper, concentrates on JSS Problem under fuzzy approach to solve a real life tailor JSSP formulated. The scheduling problem is a very common problem of a tailor shop, such that we have to satisfy the multiple conflicting objectives, which are to Minimize the job lateness or tardinessand Maximize the customer satisfactionin the best possible manner.  Here we try to find out an optimal scheduling sequence to perform the jobs that arrive at the shop.

            In this paper, the customer priority is based on the �fuzzy linguistic variables �It is expressed as Bad, Low, Medium, High, Very High etc. Fuzzy sets are used for modeling uncertainty due to vagueness. Fuzzy membership functions are used to define how well a value �fits� into a fuzzy set.A new technique is proposed based on the concept of fuzzy linguistic membership functions. This JSS model is more practical and realistic in manufacturing areas. Numerical example is given to demonstrate the effectiveness of the new developed model.



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