FUZZY NON-LINEAR OPTIMIZATION MODEL FOR PRODUCTION LINE BALANCING OF JADHAV INDUSTRIES USING GENETIC ALGORITHM
International Journal of Advanced Research in Computer Science
In a manufacturing industry production line balancing poses a significant challenge owing to the trade-off between machine idle time and Work-In-Process accumulation between different machines. Several models have been proposed to solve the problem thereby improving the line efficiency. The lowest common denominator in all such approaches is to attain an optimal level of service keeping the total cost associated with service cost and the waiting cost at its minimum. Most of the models proposed
... ill date employ hard computing techniques which poses high mathematical complexity as the number of machines in the line increase. Hard computing techniques are tolerable to moderate sized production lines and break when the size of the line increases beyond the limits. To address this issue, several soft computing techniques have been devised in literature which are logical in nature in contrast to the mathematical nature of hard computing counter parts. Further, soft computing techniques have the power of reducing NP-Hard problems to be solvable in polynomial time. In the current paper, the authors have applied nonlinear fuzzy-GA optimization model for solving production line balancing problem of Jadhav Industries Pvt. Ltd, Kolhapur. The results obtained are compared with their crisp counterparts.