Abstract: Aiming at the problem of low computational efficiency of sequential quadratic programming (SQP) algorithms when dealing with semi-infinite minimax discretization problems with complex structures and large nonlinearities, we proposed a non-monotonic sequential quadratic constrained quadratic programming (SQCQP) algorithm, and proved the convergence of the algorithm under appropiate conditions. The results of numerical experiments show that the non-monotonic SQCQP algorithm is better than the SQP algorithm in reducing the number of iterations and calculation time when the discrete level is 100.

Key words: minimax problem, norm-relaxed, strongly sub-feasible,  , SQCQP algorithm, non-monotonic technique