One of the new trends in genetic fuzzy systems (GFS) is the use of evolutionary multiobjective optimization (EMO) algorithms. This is because EMO algorithms can easily handle two conflicting objectives (i.e., accuracy maximization and complexity minimization) when we design accurate and compact fuzzy rule-based systems from numerical data. Since the main advantage of fuzzy rule-based systems co...

An extensive body of literature has indicated that there is increased activity in the frontoparietal control network (FPC) and decreased activity in the default mode network (DMN) during working memory (WM) tasks. The FPC and DMN operate in a competitive relationship during tasks requiring externally directed attention. However, the association between this FPC-DMN competition and performance i...

This paper examines the effect of mating restriction on the search ability of EMO algorithms. First we propose a simple but flexible mating restriction scheme where a pair of similar (or dissimilar) individuals is selected as parents. In the proposed scheme, one parent is selected from the current population by the standard binary tournament selection. Candidates for a mate of the selected pare...

One advantage of evolutionary multiobjective optimization (EMO) algorithms over classical approaches is that many non-dominated solutions can be simultaneously obtained by their single run. This paper shows how this advantage can be utilized in genetic rule selection for the design of fuzzy rulebased classification systems. Our genetic rule selection is a two-stage approach. In the first stage,...

In the past few years, multi-objective optimization (MOO) algorithms have been extensively applied in several fields including engineering design problems. A major reason is the advancement of evolutionary multi-objective optimization (EMO) algorithms that are able to find a set of non-dominated points spread on the respective Pareto-optimal front in a single simulation. Besides just finding a ...

Constructing an evolutionary engine platform in evolvable hardware (EHW) is one of the most important topics, and a sophisticated architecture for the application of adaptive hardware is the key for the platform. In real world, most applications are multi-objective, and it is much necessary to solve the multi-objective problems (MOPs) by implementing evolutionary multi-objective optimization (E...

In this chapter, we discuss the application of evolutionary multiobjective optimization (EMO) to association rule mining. Especially, we focus our attention on classification rule mining in a continuous feature space where the antecedent and consequent parts of each rule are an interval vector and a class label, respectively. First we explain evolutionary multiobjective classification rule mini...

The focus of this paper is the handling of overlapping solutions in evolutionary multiobjective optimization (EMO) algorithms. In the application of EMO algorithms to some multiobjective combinatorial optimization problems, there exit a large number of overlapping solutions in each generation. We examine the effect of removing overlapping solutions on the performance of EMO algorithms. In this ...

EMO syndrome is a rare extrathyroid syndrome, seen in only 1% of patients affected by extrathyroid complications of Graves' disease. A 73-year-old woman presented with a 1-year history of asymptomatic local swellings on her legs and feet. Physical examination revealed moderate proptosis and multiple, firm subcutaneous nodules of 1 to 5 cm in diameter located on the anterior and medial aspects o...

The evaluation of the temperature effect on the competitiveness between the amine addition and the amidation reaction in a model cure acid-catalysed reaction between the epoxidized methyl oleate (EMO), obtained from high oleic sunflower oil, and aniline is reported. The study was carried out analysing the kinetic profiles of the chemical species involved in the system, which were obtained apply...