Constrained nonlinear optimization problems are well known as very difficult problems. In this paper, we present a new algorithm for solving such problems. Our proposed algorithm combines the Branch-and-Bound algorithm and Lipschitz constant to limit the search area effectively; this is essential for solving constrained nonlinear optimization problems. We obtain a more appropriate Lipschitz constant by applying the formula manipulation system of each divided area. Therefore, we obtain a better approximate solution without using a lot of searching points. The efficiency of our proposed algorithm has been shown by the results of some numerical experiments.

https://file.scirp.org/pdf/AM20121100004_26797581.pdf

Tsutomu Shohdohji

Papers

An algorithm for obtaining global optima for multi-variable multi-model functions

An algorithm for obtaining a global optimum for one variable multi-modal functions