I almost laughed out loud - for several decades almost no-one worked on multiple-objective optimization, and those who did in the 70s and 80s did not have good tools - or the theory. So you say that now almost everyone does? I don't believe you. And I am not saying that working on multiple-objective optimization is not fruitful, just that I do think that most scientists working with optimization models still worry about only one objective. You see - even just one objective can be a very, very tricky thing to handle. :-)

So, Josimar - what ideas do you have?

First, I want to connect with the people who is working these algorithms. After, exchange ideas and problems to each other and start to perform experiments to compare and test ideas.

O.K. Please, tell us about your research field and types of optimization models you apply.

I can summarize my work according to applications: - benchmark functions(ackley, rastrigin, rosenbrock, schweffel, sphere) - initialization of multilayer perceptron for regression, pattern recognition and classification - protein folding - knapsack problem using local search inspired in chaos search - some multi-objective problems