Implementation of polynomial multi-objective optimization in Mathematica
We describe implementation of main methods for solving polynomial multi-objective optimization problems by means of symbolic processing available in the programming language MATHEMATICA. Symbolic transformations of unevaluated expressions, representing objective functions and constraints, into the corresponding representation of the single-objective constrained problem are especially emphasized. We also describe a function for the verification of Pareto optimality conditions and a function for graphical illustration of Pareto optimal points and given constraint set.
mathematica multiple-objective programming weighting coefficients prioritizing methods goal programming