IN THIS PAPER, WE FIRST INVESTIGATE THE Optimization OF Convex FUNCTIONS BY USING LAGRANGE MULTIPLIERS AND SADDLE POINTS.NEXT, WE PRESENT AN ALGORITHM FOR FINDING THE GLOBAL MAXIMIZERS OF THE CONSTRAINED NON-POSITIVE VALUED ICR (INCREASING AND CO-RADIANT) FUNCTIONS OVER THE UNIT SIMPLEX BY USING THE GLOBAL MAXI-MIZERS OF INCREASING AND POSITIVELY HOMOGENEOUS (IPH) FUNCTIONS.ALSO, WE GIVE SOME NUMERICAL EXPERIMENTS. FINALLY, NON-POSITIVE VALUED AFFINE ICR FUNCTIONS ARE DEFINED IN THE FRAMEWORK OF ABSTRACT ConvexITY. THE BASIC PROPERTIES OF THIS CLASS OF FUNCTIONS SUCH AS SUPPORT SET AND SUB DIFFERENTIAL ARE PRESENTED. AS AN APPLICATION, WE GIVE OPTIMALITY CONDITIONS FOR THE GLOBAL MINIMUM OF THE DIFFERENCE OF TWO STRICTLY NON-POSITIVE VALUED AFFINE ICR FUNCTIONS.