本研究以FORTRAN程式與ANSYS有限元素分析軟體中的APDL語法結合成一系統程式。並透過六個不同範例驗證了PSO-SA混合法於結構多目標最佳化設計上皆有不錯之成效。 The PSO-SA hybrid method was applied to multiobjective optimum design of structure in this study. Particle Swarm Optimization is to mimic the behavior of birds finding a good path to the food, which is one of the artificial biological algorithms. Thus, it has the merits of converge efficiently and programming easily. The advantage of Particle Swarm Optimization (PSO) is it global search technique. The Simulated Annealing (SA) method is based on the principle of statistical thermodynamic. That is material during the annealing process can be reached most cryogenic state phenomenon. The possibility of local optimum jump to global optimum can be determined by the probability of the Bozeman function. The structural optimization problem can be transformed into a mathematical function. The new design can be obtained by using the linear decreasing inertia weight to update velocity and position of particles. After the optimal solution was obtained, the strategy of SA method is initiated to determine whether this optimal solution should be neglected or not . In the Numerical examples, the study showed that the computational efficiency can be improved and the constraint is satisfied. A systematic program was developed by FORTRAN and APDL of ANSYS software. The optimum results of six different multiobjective examples showed that the PSO-SA hybrid methods are reasonable compared to other references.