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In recent years,simulated annealing algorithms have been extensively developed and utilized to solve multi-objective optimization problems.In order to obtain better optimization performance,this paper proposes a Novel Adaptive Simulated Annealing (NASA) algorithm for constrained multiobjective optimization based on Archived Multiobjective Simulated Annealing (AMOSA).For handling multi-objective,NASA makes improvements in three aspects:sub-iteration search,sub-archive and adaptive search,which effectively strengthen the stability and efficiency of the algorithm For handling constraints,NASA introduces corresponding solution acceptance criterion.Furthermore,NASA has also been applied to optimize TD-LTE network performance by adjusting antenna parameters; it can achieve better extension and convergence than AMOSA,NSGAII and MOPSO.Analytical studies and simulations indicate that the proposed NASA algorithm can play an important role in improving multi-objective optimization performance.