The article addresses the n-job, non-preemptive and single machine scheduling problem of minimizing the sum of earliness and tardiness with different release times and due dates. To solve the problem, it proposes a hybrid genetic algorithm with a new crossover and mutation operators to adjust the job sequencing. To investigate the suitability of the parameters set and the quality of the solution, the article evaluates the number of corresponding solutions and the speed of converging to an optimal solution which is solved by an enumeration method for small size problems. To demonstrate the performance of the proposed GA, it is empirically evaluated by solving a large number of problems and compared with solutions obtained by genetic algorithms using the existing operators.
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