Authors:
Nicole Drechsler
1
;
Andre Sülflow
2
and
Rolf Drechsler
3
Affiliations:
1
University of Bremen, Germany
;
2
solvertec GmbH, Germany
;
3
University of Bremen and DFKI GmbH, Germany
Keyword(s):
Many-Objective Optimization, Nurse Rostering Problem, Relation ε-Preferred, User Preferences.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Computational Intelligence
;
Evolutionary Computing
;
Evolutionary Multiobjective Optimization
;
Soft Computing
Abstract:
During the last 10 years, many-objective optimization problems, i.e. optimization problems with more than
three objectives, are getting more and more important in the area of multi-objective optimization. Many real-
world optimization problems consist of more than three mutually dependent subproblems, that have to be
considered in parallel. Furthermore, the objectives have different levels of importance. For this, priorities
have to be assigned to the objectives. In this paper we present a new model for many-objective optimization
called Prio-ε-Preferred, where the objectives can have different levels of priorities or user preferences. This
relation is used for ranking a set of solutions such that an ordering of the solutions is determined. Prio-ε-
Preferred is controlled by a parameter ε, that is problem specific and has to be adjusted experimentally by the
designer. Therefore, we also present an extension called Adapted-ε-Preferred (AEP), that determines the ε
values automatically
without any user interaction. To demonstrate the efficiency of our approach, experiments
are performed.
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