Any manufacturing system has to attain the key performance measures for its successful operation. Quality Function Deployment (QFD) is to convert the customer requirements into “quality characteristics” and develop a schedule for the jobs by systematically deploying the relationships between the due date and the completion time by adopting the just in time concept. A generalized model for analyzing the manufacturing system is essential to improve the performance measures. Non - traditional optimization technique such as Simulated Annealing (SA) technique provides a complete solution methodology for solving the shop floor scheduling problems. The problem considered in this study consists of identical and non-identical machines arranged in parallel. Jobs ranging from 10 to 100 are to be processed on the machines and the objective is to reduce the multiple objectives such as the earliness and the tardiness measures of the completed jobs. The proposed simulated annealing technique identifies the optimal sequences for the different weighted, earliness and tardiness combinations. It has been observed that the suggested optimization procedure arrives at the optimal solution at a reasonable computation time. The performance of the proposed method has been compared with the existing heuristics and is found to outperform it.