A new accelerating method for globally solving a class of nonconvex programming problems

Abstract In this paper, we combine the new global optimization method proposed by Jiao [H. Jiao, A branch and bound algorithm for globally solving a class of nonconvex programming problems, Nonlinear Anal. 70 (2) (2008) 1113–1123] with a suitable deleting technique to propose a new accelerating global optimization algorithm for solving a class of nonconvex programming problems (NP). This technique offers a possibility to cut away a large part of the currently investigated region in which the global optimal solution of NP does not exist, and can be seen as an accelerating device for the global optimization algorithm of the nonconvex programming problems. Compared with the method in the above cited reference, numerical results show that the computational efficiency is obviously improved by using this new technique in the number of iterations, the required list length and the overall execution time of the algorithm.

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