A novel one-parameter filled function method with an application to pathological analysis.

The filled function method is an efficient approach for finding a global minimizer of global optimization problems. The key of this kind of methods is the design of filled function. In this paper, we propose a new filled function with one parameter that is continuously differentiable and always contains local information of objective function. Then, a new filled function method involved the proposed filled function for unconstrained global optimization problems is developed. Furthermore, numerical experiments are conducted to demonstrate the efficiency and reliability of our algorithm. We finally apply the proposed algorithm to study the pathological factors in renal cell carcinoma metastasis. [ABSTRACT FROM AUTHOR]