Citation:
S.V. Utyuzhnikov, P. Fantini and M.D. Guenov, A method for generating a well-distributed Pareto set in nonlinear
multiobjective optimization, Journal of Computational and Applied Mathematics,
Volume 223, Issue 2, 15 January 2009, Pages 820-841.
Abstract:
A method is presented for generating a well-distributed Pareto set in nonlinear
multiobjective optimization. The approach shares conceptual similarity with the
Physical Programming-based method, the Normal-Boundary Intersection and the
Normal Constraint methods, in its systematic approach investigating the
objective space in order to obtain a well-distributed Pareto set. The proposed
approach is based on the generalization of the class functions which allows the
orientation of the search domain to be conducted in the objective space. It is
shown that the proposed modification allows the method to generate an even
representation of the entire Pareto surface. The generation is performed for
both convex and nonconvex Pareto frontiers. A simple algorithm has been proposed
to remove local Pareto solutions. The suggested approach has been verified by
several test cases, including the generation of both convex and concave Pareto
frontiers.