I mean if you browse the issues of some famous journals on evolutionary computation such as IEEE Transaction on EC, you'll find that most of the papers are on subject of multi-criteria optimization in the past 2 or 3 years. Why?
Good question,
I can think of the following:
1) ECs are Pareto based algorithms and perform betters than methods which convert the MO problem to SO (like weighted)
2) Tthere are many SO applications in this journal in the past decade, therefore the subject might saturated!
3) Any constrained SO problem can be formulated as SO
I hope this helps
I fully agree with Ka-Chun Wong and Behrouz Ahmadi-Nedushan. Additionally I would like to mention the should be look towards solving an Engineering Optimization problem. Almost every practical problem is associated with some constraints and some other problems and thus solving these problems needs great care. Almost every two related (means, to solve one independently would be impractical in many sense) problems are Multi-modal, non-separable and typically mathematically un-correlated (unless a strong such correlation is established, which is often very rare) but practically correlated. These set up multiple objectives and criteria. Thus, a need for multi-objective and multi-criteria based optimization is evident. This is a great advancement of EC community towards solving engineering problems.
I completely agree with the above suggestions. Actually, if you notice any real life problem closely, you could see that those problems somehow related to the optimization and most importantly those are multi-objective optimization. Just take an example if a problem is related to a product, we always want to maximize its productivity whether we have to maintain a descent cost also ; so, this is multi-objective and probably that's the main reason why this topic shines...
This is because all real problems present conflictive scenarios. Therefore, they can be formulated as multiobjective.
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