Recently, Gregório and Oliveira developed a proximal point scalarization method (applied to multiobjective optimization problems) for an abstract strict scalar representation with a variant of the logarithmic-quadratic function of Auslender et al. as regularization. In this work we propose a variation of this method, taking into account the regularization with logarithm and quasi-distance, wher...

Higher order mutation testing is considered a promising solution for overcoming the main limitations of first order mutation testing. Strongly subsuming higher order mutants (SSHOMs) are the most valuable among all kinds of higher order mutants (HOMs) generated by combining first order mutants (FOMs). They can be used to replace all of its constituent FOMs without scarifying test effectiveness....

Abstract The Chaos Game Optimization (CGO) has only recently gained popularity, but its effective searching capabilities have a lot of potential for addressing single-objective optimization issues. Despite advantages, this method can tackle problems formulated with one objective. multi-objective CGO proposed in study is utilized to handle the several objectives (MOCGO). In MOCGO, Pareto-optimal...

We propose three operators based on MFF. The first uses MFF. The second uses MFF when applies Maximin-Constraint and uses modified MFF when applies Maximin-Clustering. The third uses modified MFF. According to the results, the three operators are competitive to solve multi-objective optimization problems having both low dimensionality (two or three) and high dimensionality (more than three) in ...

In the paper, the problem of multi-objective (MOBJ) learning is discussed. The problem of obtaining apparent (effective) complexity measure, which is one of the objectives, is considered. For the specific case of RBFN, the bounds on the smoothness-based complexity measure are proposed. As shown in the experimental part, the bounds can be used for Pareto set approximation.

While solution methods are well-known for optimization problems with a single objective function, there are many common real world scenarios in which a single function does not suffice. Multiobjective or multicriteria optimization is the branch of optimization that deals with the case of two or more objective functions. An important example is the biobjective problem that arises in portfolio op...