peer reviewedIn this work we focus on defining how dynamism can be modeled in the context of multi-objective optimization. Based on this, we construct a component oriented classification for dynamic multi-objective optimization problems. For each category we provide synthetic examples that depict in a more explicit way the defined model. We do this either by positioning existing synthetic benchmarks with respect to the proposed classification or through new problem formulations. In addition, an online dynamic MNK-landscape formulation is introduced together with a new comparative metric for the online dynamic multi-objective context
Abstract. Many practical, real-world applications have dynamic features. If the changes in the fitne...
Dynamic multiobjective optimisation deals with multiobjective problems whose objective functions, se...
Decomposition-based multi-objective evolutionary algorithms provide a good framework for static mult...
The file attached to this record is the author's final peer reviewed version. The Publisher's final ...
Dynamic multi-objective optimization has received increasing attention in recent years. One of strik...
Dynamic multi-objective optimization problems (DMOPs) are optimization problems where elements of th...
Abstract. Dynamic optimization using evolutionary algorithms is receiving increasing interests. Howe...
Dynamic multi-objective optimization has received growing research interest in recent years since ma...
Dynamic optimization using evolutionary algorithms is receiving increasing interests. However, typic...
The file attached to this record is the author's final peer reviewed version. The Publisher's final ...
Many real-world optimization problems appear to not only have multiple objectives that conflict each...
This paper proposes an approach, called Multi-objective Algorithm for Dynamic Environments (MADE), w...
The file attached to this record is the author's final peer reviewed version. The Publisher's final ...
Dynamic multi-objective optimization plays an important role in planning and decision-making. This c...
In many real world problems the quality of solutions needs to be evaluated at least according to a b...
Abstract. Many practical, real-world applications have dynamic features. If the changes in the fitne...
Dynamic multiobjective optimisation deals with multiobjective problems whose objective functions, se...
Decomposition-based multi-objective evolutionary algorithms provide a good framework for static mult...
The file attached to this record is the author's final peer reviewed version. The Publisher's final ...
Dynamic multi-objective optimization has received increasing attention in recent years. One of strik...
Dynamic multi-objective optimization problems (DMOPs) are optimization problems where elements of th...
Abstract. Dynamic optimization using evolutionary algorithms is receiving increasing interests. Howe...
Dynamic multi-objective optimization has received growing research interest in recent years since ma...
Dynamic optimization using evolutionary algorithms is receiving increasing interests. However, typic...
The file attached to this record is the author's final peer reviewed version. The Publisher's final ...
Many real-world optimization problems appear to not only have multiple objectives that conflict each...
This paper proposes an approach, called Multi-objective Algorithm for Dynamic Environments (MADE), w...
The file attached to this record is the author's final peer reviewed version. The Publisher's final ...
Dynamic multi-objective optimization plays an important role in planning and decision-making. This c...
In many real world problems the quality of solutions needs to be evaluated at least according to a b...
Abstract. Many practical, real-world applications have dynamic features. If the changes in the fitne...
Dynamic multiobjective optimisation deals with multiobjective problems whose objective functions, se...
Decomposition-based multi-objective evolutionary algorithms provide a good framework for static mult...