Theory, computation, and practice of multiobjective optimisation

we decided to organise a special issue on theory, computation, and practice of multiobjective optimisation.Since at the two conferences many presentations addressed a variety of different multiobjective optimisation problems, we decided to focus this special issue distinctively on recent developments in multiobjective optimisation falling within the a posteriori paradigm of multiple criteria decision making (MCDM).Motivated by the prevalence of presentations on this topic, our goal was to give the international community an opportunity to publish papers proposing models, methods, and algorithms for multiobjective optimisation and their supporting mathematical theory.In addition, to make the future volume appealing to scientists, engineers, and practitioners, the final call for papers also asked for manuscripts describing important applications of multiobjective optimisation in practice.In total, we received 38 submissions for this issue.Of these submissions, 15 papers were out of scope by addressing other topics in the MCDM area; 9 papers were rejected following reviews; 1 paper was withdrawn by the authors during the review process; and 13 papers were accepted.These 13 papers constitute this special issue.The topics addressed in these papers follow the recent trends observed in the optimisation area in general.The type of optimisation problems addressed ranges from scheduling problems with two objectives to mixed integer linear optimisation problems and nonlinear optimization problems, both with only continuous and with continuous as well as binary variables.Some multiobjective models are specifically bi-or tri-objective while the methods include exact, heuristic, or hybrid algorithms to compute or approximate the Pareto set of these problems.Exact methods are typically used for small-size problems while heuristic or hybrid algorithms are designed for large-scale instances for which they prove to be competitive.The presented applications reflect the type of decision-making situations that are important but challenging and therefore of interest to researchers.