The stochastic manufacturing system has one or more random variables as inputs that lead to random outputs. Since the outputs are random, they can be considered only as estimates of the true characteristics of the system. These estimates could greatly differ from the corresponding real characteristics for the system. Multiple replications are necessry to get reliable information on the system and output data should be analyzed to get optimal solution. It requires too much computation time prac cally. In this paper a GA method, named Stochastic Genetic Algorithm(SGA) is proposed and tested to find the optimal solution fast and efficiently by reducing the number of replications.
1. Introduction
2. Literature review
3. Stochastic Genetic Algorithm
4. Experiments
5. Conclusion
Reference