An algorithm for approximating nondominated points of convex multiobjective optimization problems

ýIn this paperý, ýwe present an algorithm for generating approximate nondominated points of a multiobjective optimization problem (MOP)ý, ýwhere the constraints and the objective functions are convexý. ýWe provide outer and inner approximations of nondominated points and prove that inner approximations provide a set of approximate weakly nondominated pointsý. ýThe proposed algorithm can be applied for differentiable or nondifferentiable convex MOPsý. ýTo illustrate efficiency of the proposed algorithm for convex MOPsý, ýwe provide numerical examples.