Journal of Optimization Theory and Applications
On Finding the Maxima of a Set of Vectors
Journal of the ACM (JACM)
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Characterization of variable domination structures via nonlinear scalarization
Journal of Optimization Theory and Applications
On the Performance Assessment and Comparison of Stochastic Multiobjective Optimizers
PPSN IV Proceedings of the 4th International Conference on Parallel Problem Solving from Nature
Constrained Test Problems for Multi-objective Evolutionary Optimization
EMO '01 Proceedings of the First International Conference on Evolutionary Multi-Criterion Optimization
Multicriteria Optimization
Vector optimization problems with nonconvex preferences
Journal of Global Optimization
Variable preference modeling with ideal-symmetric convex cones
Journal of Global Optimization
A framework for incorporating trade-off information using multi-objective evolutionary algorithms
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part II
Reducing the run-time complexity of multiobjective EAs: The NSGA-II and other algorithms
IEEE Transactions on Evolutionary Computation
A review of multiobjective test problems and a scalable test problem toolkit
IEEE Transactions on Evolutionary Computation
Hi-index | 0.00 |
Decision making in the presence of multiple and conflicting objectives requires preference from the decision maker. The decision maker's preferences give rise to a domination structure. Till now, most of the research has been focussed on the standard domination structure based on the Pareto-domination principle. However, various real world applications like medical image registration, financial applications, multicriteria n-person games, among others, or even the preference model of decision makers frequently give rise to a so-called variable domination structure, in which the domination itself changes from point to point. Although variable domination is studied in the classical community since the early seventies, we could not find a single study in the evolutionary domain, even though, as the results of this paper show, multi-objective evolutionary algorithms can deal with the vagaries of a variable domination structure. The contributions of this paper are multiple-folds. Firstly, the algorithms are shown to be able to find a well-diverse set of the optimal solutions satisfying a variable domination structure. This is shown by simulation results on a number of test-problems. Secondly, it answers a hitherto open question in the classical community to develop a numerical method for finding a well-diverse set of such solutions. Thirdly, theoretical results are derived which facilitate the use of an evolutionary multi-objective algorithm. The theoretical results are of importance on their own. The results of this paper adequately show the niche of multi-objective evolutionary algorithms in variable preference modeling.