Balancing Spare Parts Demand in the Automobile Sector -A Case Study : Spare parts management,Introduction,Regression analysis,Markov chain,Genetic algorithm

In this work,forecasting techniques like Simple moving average, Simple and linear regression is used. A simple moving average is method of computing the average of a specified number of the most recent data values in a series to determine the minimal demand rate. Simple linear regression is a way to describe a relationship between two variables through an equation of straight line, called line of best fit, that most closely models this relationship. we have developed a new and efficient approach that works on Genetic Algorithms in order to distinctively determine the availability of the spares by week after week ,here the two parent chromosomes are randomly generated for each time from the data collected from the automobile sector, then these parent chromosomes are subjected to cross-over operation and mutation operation to create new off-springs(children) then from the off-springs generated the off-spring which is having the more fitness value will be selected from the roulette wheel selection. So, by means of that we can estimate which type of stock pattern is healthy for automobile sector is identified.