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Jobshop manufacturing system is a suitable system for economical manufacturing of parts family and Jobshop scheduling is completely efficient in successfully running in improvement of productivity of system. The jobshop scheduling model has multiple objectives: Minimizing makes pan (Cmax) and Minimizing the Weighted Sum of Earliness and Tardiness penalties (WSET). In this study to achieve these objectives at the same time, Goal Programming (GP) has being used. This model from as computational point of view is NP-Hard, so in this paper we apply the Simulated Annealing (SA) meta-heuristic approach for solve it. One array structure of solution (family parts or parts in family) is used in common methods that lead to decrease of solution space, but in this study hybrid selection of neighborhood structures has been used for determaine the structure of solution; Directed Interchange Scheme (DIS) and Random Interchange Scheme (RIS). The results of research indicate solving goal programming model of Job shop Scheduling by SA is efficient to achieve goals of model.