Metaheuristics for multi-objective optimization
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A substantial number of metaheuristics for multi-objective 
problem solving has been proposed so far, and an attempt 
of unifying existing approaches is here presented. Based 
on a fine-grained decomposition and following the main 
issues of fitness assignment, diversity preservation and 
elitism, a conceptual global model is proposed and is validated 
by regarding a number of state-of-the-art algorithms as 
simple variants of the same structure.

The presented model is then incorporated into a general-purpose 
software framework dedicated to the design and the implementation 
of evolutionary multi-objective optimization techniques: ParadisEO-MOEO. 
This package has proven its validity and flexibility by enabling 
the resolution of many real-world and hard multi-objective 
optimization problems.