Researchers from Gyeongsang National University Describe Findings in Global Optimization

According to recent research from South Korea, "In this paper, we consider a differentiable multiobjective optimization problem with generalized cone constraints (for short, MOP)."

"We investigate the relationship between weakly efficient solutions for (MOP) and for the multiobjective optimization problem with the modified objective function and cone constraints [for short, (MOP) (eta) (x)] and saddle points for the Lagrange function of (MOP) (eta) (x) involving cone invex functions under some suitable assumptions. We also prove the existence of weakly efficient solutions for (MOP) and saddle points for Lagrange function of (MOP) (eta) (x) by using the Karush-Kuhn-Tucker type optimality conditions under generalized convexity functions," wrote J.W. Chen and colleagues, Gyeongsang National University.

The researchers concluded: "As an application, we investigate a multiobjective fractional programming problem by using the modified objective function method."

Chen and colleagues published their study in the Journal of Global Optimization (Multiobjective optimization problems with modified objective functions and cone constraints and applications. Journal of Global Optimization, 2011;49(1):137-147).

For additional information, contact Y.J. Cho, Gyeongsang National University, Dept. of Math Education, Chinju 660701, South Korea.

Publisher contact information for the Journal of Global Optimization is: Springer, Van Godewijckstraat 30, 3311 Gz Dordrecht, Netherlands.