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A novel approach to solve equal size lot streaming (ESLS) in job-shop scheduling problem (JSP) using genetic algorithms (GA) is proposed. LS refer to a situation that a lot can be split into a number of smaller lots (or sub-lots) so that successive operation can be overlapped. By adopting the proposed approach, the sub-lot number for different lots and the processing sequence of all sub-lots can be determined simultaneously using GA. Applying just-in-time (JIT) policy, the results show that the solution can minimize both the overall penalty cost and total setup time with the development of multi-objective function. In this connection, decision makers can then assign various weightings so as to enhance the reliability of the final solution.