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Social learning in particle swarm optimization (PSO) helps collective efficiency, whereas individual reproduction in genetic algorithm (GA) facilitates global effectiveness. This observation recently leads to hybridizing PSO with GA for performance enhancement. However, existing work uses a mechanistic parallel superposition and research has shown that construction of superior exemplars in PSO is...
The self-adaptive genetic algorithm, its main thought is to let control parameter (population, hybridization rate and mutation rate) adjusted adaptively within the proper range find the best parameter of the corresponding problem, thus received optimum which has stronger adaptability. It is proved that the self-adaptive genetic algorithm is with excellent convergence and higher precision than the...
First pioneered by John Holland in the 60s, Genetic Algorithms has been widely studied, experimented and applied in many fields in the real world. The correlated courses have been offered at many universities. However, the teaching methods for the algorithm are not sufficient. This paper proposes an experimental tool for the teaching of the genetic algorithm. The traveling salesman problem is conducted...
Reasonable scanning task scheduling strategy can improve the scanning efficiency of vulnerability detection systems at a large extent. Task scheduling problem has been proved to be an NP-complete problem. Based on the request and characteristics of vulnerability detection technology, this paper establishes a distributed scanning task scheduling model, and describes a scanning task distributing algorithm...
In power grid, we focus on one kind of high performance computing applications, that is, power system computing and Simulation (PCS) applications. PCS applications are always broken down into several sub-tasks depending on each other, which can be represented as a DAG. Genetic algorithm (GA) has been widely used to solve the dependent tasks scheduling. However the conventional GA is too slow to be...
Researches in the ant colony optimization algorithm has been expanding rapidly both in academia and industry. The correlated courses have been offered at many universities. However, the teaching methods for the algorithm are not sufficient. This paper proposes an experimental tool for the teaching of the ant colony optimization algorithm. The traveling salesman problem is conducted as the application...
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