The Estimation of Distribution Algorithms are a class of evolutionary algorithms which adopt probabilistic models to reproduce the genetic information of the next generation, instead of conventional crossover and mutation operations. In this paper, we propose new EDAs which incorporate mutation operator to conventional EDAs in order to keep the diversities in EDA populations. Experiments result...

The segmentation accuracy of Roman cursive characters, especially touched characters, is essential for the high performance of Optical Character Recognition Systems. This paper presents a new approach for non-linear segmentation of multiple touched Roman cursive characters based on genetic algorithm. Initially, a possible segmentation zone is detected and then best segmentation path is evolved ...

Insurance-linked securities portfolio with the VaR constraint optimization problem have a kind of weak dominance or ordering property, which enables us to reduce the variables’ dimensions gradually through exercising a genetic algorithm with randomly selected initial populations. This property also enables us to add boundary attraction potential to GA-MPC’s repair operator, among other modifica...

In recent years the use of Genetic or Evolutionary techniques has produced interesting results on the automatic generation of Knowledge Bases for Fuzzy Logic Controllers. Three diierent representations of the rule base have been considered: list of rules, relational matrix and decision table. The use of lists of rules reduces the dimension of the rule base but presents some handicaps for crosso...

The heavy-tailed mutation operator proposed in Doerr et al. (GECCO 2017), called fast to agree with the previously used language, so far was proven be advantageous only mutation-based algorithms. There, it can relieve algorithm designer from finding optimal rate and nevertheless obtain a performance close one that gives. In this first runtime analysis of crossover-based using choice rate, we sh...

Genetic algorithms (GAs) generate solutions to optimization problems using techniques inspired by natural evolution, like crossover, selection and mutation. In that process, crossover operator plays an important role as an analogue to reproduction in biological sense. During the last decades, a number of different crossover operators have been successfully designed. However, systematic comparis...

In this paper, we propose a technique for the application of the crossover operator that generates multiple descendants from two parents and selects the two best offspring to replace the parents in the new population. In order to study the proposal, we present different instances based on the BLX-α crossover operator for real-coded genetic algorithms. In particular, we investigate the influence...

Constellation design is a typical multiple peaks, multiple valleys and non-linear multi-objective optimization problem. How to design satellite constellation is one of the key sectors of research in the aerospace field. In this paper, in order to improve the global convergence and diversity performance of traditional constellation optimization algorithm, multi-parent arithmetic crossover and SB...

Under the background of increasing pressure satellite communication support, reasonable and efficient dispatch resources is an important means to improve utilization efficiency resources. Aiming at resource scheduling task requirements geostationary orbit system, (CSRS) model established first all, based on this, advances a kind CSRS method improved whale optimization algorithm. In this method,...