Lexicographic improvement of the target values in convex goal programming

The aim of this paper is to carry out an exhaustive post optimization analysis in a Convex Goal Programming problem, so as to study the possible existence of satisfying solutions for different levels of the target values. To this end, an interactive algorithm is proposed, which allows us to improve the values of the objective functions, after obtaining a satisfying solution, if such a solution exists, in such a way that a Pareto optimal solution is finally reached, through a successive actualization of such target values. This way, the target values are lexicographically improved, according to the priority order previously given by the decision maker, in an attempt to harmonize the concepts of satisfying and efficient solutions, which have traditionally been in conflict.