Selection of Job Shop
Scheduling Problem Using Fuzzy Linguistic Variables.
Vikas S. Jadhav1
and V. H. Bajaj2
Student, 2Professor} Department of Statistics,
Dr.B.A.M.University, Aurangabad-431004(M.S) INDIA.
Academic Editor: Dr.
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 tardiness� and �Maximize the customer
satisfaction� in the best possible manner. Here we try
�to find out an optimal scheduling sequence to perform the
jobs that arrive at the shop�.
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
new technique is proposed based on the concept of fuzzy linguistic
membership functions. This JSS model is more practical and realistic in
Numerical example is
given to demonstrate the effectiveness of the new developed model.