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A Modied Feasible SQP Method for Constrained Minimax Optimization Problems 1

Zhijun Luo, Lirong Wang, Guohua Chen

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Abstract

This paper presents a modied feasible SQP algorithm for solving constrained minimax optimization problems. At each iteration of the proposed algorithm in this paper, the descent direction is yielded by solving only one quadratic programming through intro- ducing an auxiliary variable. A height-order correction direction is obtained by solving a corresponding quadratic programming. Furthermore, under some mild conditions, the global convergence and superlinear properties are proved. Finally, some numerical results reported show that the algorithm is successful.

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What this paper is about

This paper presents a modied feasible SQP algorithm for solving constrained minimax optimization problems. At each iteration of the proposed algorithm in this paper, the descent direction is yielded by solving only one quadratic programming through intro- ducing an auxiliary variable. A height-order correction direction is obtained by solving a corresponding quadratic programming. Furthermore, under some mild conditions, the global convergence and superlinear properties are proved. Finally, some numerical results reported show that the algorithm is successful.

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Available abstract

This paper presents a modied feasible SQP algorithm for solving constrained minimax optimization problems. At each iteration of the proposed algorithm in this paper, the descent direction is yielded by solving only one quadratic programming through intro- ducing an auxiliary variable. A height-order correction direction is obtained by solving a corresponding quadratic programming. Furthermore, under some mild conditions, the global convergence and superlinear properties are proved. Finally, some numerical results reported show that the algorithm is successful.

Key concepts: Sequential quadratic programming, Minimax, Mathematical optimization, Quadratic programming, Convergence (economics), Mathematics, Descent (aeronautics), Engineering

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