The development of exact methods for multi-objective optimisation is experiencing increasing interest in the OR community as witnessed by the growing body of research emerging from that domain. Recent advances in the development of nonlinear, linear and mixed integer optimisation solvers push the boundaries towards more challenging areas. Hence solving to optimality larger, more difficult (real-world) problems involving several conflicting objectives, has been put within reach. As guest editors we hope that this feature cluster increases the visibility of research concerning exact methods for multi-objective optimisation and to motivate a broader group of researchers to contribute to the field. It presents a collection of the latest research results on exact algorithms for multi-objective optimisation as well as heuristics derived from exact methods.
EHRGOTT, M., LJUBIC, I. and PARRAGH, S.N. (2017). EDITORIAL: Feature Cluster: Recent Advances in Exact Methods for Multi-Objective Optimization. European Journal of Operational Research, 260(3), pp. 805-806.