Benders decomposition for multiobjective programs with cone inclusions

Benders decomposition is a useful and efficient method to solve optimization problems such that the variables can be divided into two sets. The original decomposition scheme handles only mixed-variables problems, i.e. problems with linear and integer variables. In this article we show a generalization of the decomposition method for multiobjective programs which contain cone inclusions as constraints and there is only a weak assumption on the complicating variables. The algorithm is a frame that needs a subroutine solving cone problems exactly.