Particle Swarm Optimization (PSO) is a global optimization algorithm for real valued problems. One of the known positive traits of the algorithm is fast convergence. While this is considered a good thing because it means the solutions are found faster it can lead to stagnation at a local minimum. There are several strategies to circumvent this. One of them is the use of mutation operators to in...

The functional significance of a lac operator constitutive mutation has been determined. The transition adenine-thymine to guanine-cytosine was shown to be a constitutive mutation simply because thymine contains the functionally important 5-methyl group whereas cytosine does not. The remainder of the base pair is of no consequence. The experimental approach was to synthesize various modified op...

in this paper we study properties of symbols such that these belong to class of symbols sitting insidesm ρ,φ that we shall introduce as the following. so for because hypoelliptic pseudodifferential operatorsplays a key role in quantum mechanics we will investigate some properties of m−hypoelliptic pseudodifferential operators for which define base on this class of symbols. also we consider maxi...

This paper proposes the use of the qGaussian mutation with self-adaptation of the shape of the mutation distribution in evolutionary algorithms. The shape of the q-Gaussian mutation distribution is controlled by a real parameter q. In the proposed method, the real parameter q of the q-Gaussian mutation is encoded in the chromosome of individuals and hence is allowed to evolve during the evoluti...

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...

In real-world production processes, the same enterprise often has multiple factories or one factory lines, and objectives need to be considered in process. A dual-population genetic algorithm with Q-learning is proposed minimize maximum completion time number of tardy jobs for distributed hybrid flow shop scheduling problems, which have some symmetries machines. Multiple crossover mutation oper...

Differential evolution (DE) is an efficient and robust evolutionary algorithm and has wide application in various science and engineering fields. DE is sensitive to the selection of mutation and crossover strategies and their associated control parameters. However, the structure and implementation of DEs are becoming more complex because of the diverse mutation and crossover strategies that use...

We investigate the effect of restricting the mutation operator in evolutionary algorithms with respect to the runtime behavior. For the Eulerian cycle problem; we present runtime bounds on evolutionary algorithms with a restricted operator that are much smaller than the best upper bounds for the general case. It turns out that a plateau that both algorithms have to cope with is left faster by t...