A large number of the real world planning problems which are today solved using Operations Research methods are actually multi-objective planning problems, but most of them are solved using single-objective methods. The reason for converting, i.e. simplifying, multi- objective problems to single-objective problems is that no standard multi-objective solvers exist and specialized algorithms need to be programmed from scratch. In this article we will present a hybrid approach, which both operate in decision space and in objective space. The approach enables massive efficient parallelisation and can be used to a vide variety of bi-objecive Mixed Integer Programming models. We test the approach on the biobjejctive extension of the classic traveling salesman problem, on the standard dataset, and determine for the full set of nondominated points. This has only been done once before [1], and in our approach we do it in a fraction of the time.
Citation
Unpublished DTU-Management Engineering Technical University of Denmark Kgs. Lyngby 2800 Denmark March 2017