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To enhance the local search capability of quantum-inspired evolutionary algorithm, a novel memetic algorithm based on real-observation quantum-inspired evolutionary algorithms (MArQ) was proposed. MArQ is a hybrid algorithm combining QIEA with local search techniques. In MArQ, QIEA was used to explore the whole solution space and tabu search was employed to exploit the neighboring domains of the searched...
Parameters setting is an important problem of evolution algorithms, include differential evolution algorithm. It has an effect on the performance of evolution algorithms. Although there is only three control parameters in differential evolution (DE) algorithm, the parameters setting is also a difficult problem. Self-adaptation is highly beneficial for adjusting the control parameters, especially when...
This paper is aimed to present a genetic algorithm focusing on the sexual selection used the Pareto based approach for solving multi-objective optimization problems. It uses a concept of sexual selection with different types of gender and mutation rates based on the sex to produce offspring. Its performance was evaluated by the well-known benchmark functions as well as also tested with a networking...
Group selection is often cited as an explanation for the survival of altruistic behaviors. The evolutionary dynamic model of altruistic behaviors is established and analyzed. The sufficient and necessary condition for the survival of altruistic behaviors is obtained and proved. Although in a single interaction the altruist is at a disadvantageous position compared with the egoist, altruistic behaviors...
A large number of multi-objective optimization evolutionary algorithms(MOEAs) have been developed in the past two decades. To compare these methods rigorously, or to measure the performance of a particular MOEA quantitatively, a variety of performance measures have been proposed. In this paper, some existing widely-used performance measures are briefly reviewed and compared according different properties...
The game model of Prisoner??s Dilemma is applied to describe the survival game between altruistic behaviors and selfish behaviors. The game model is extended to an evolutionary game. The survival conditions for altruistic behaviors are obtained. Simulation results show that altruists tend to cluster so as to improve their survival probability. The conclusions are useful to the stability study of social...
This paper proposes one of the ideas related to swarm intelligence in social insects, by using ant pheromone concepts in ant-based clustering. Multiple pheromones in ant-based clustering (MPABC) with ant nest algorithm and with ant memory algorithm are our two proposed methods of multiple pheromone concepts in ant-based clustering. Both algorithms have used the artificial pheromones which consist...
Estimation of Distribution Algorithms (EDAs) is new kinds of colony evolution algorithms. It produces its new generation by constructing probability distribution model through counting excellent information of individuals of present colony EDAs first, and then sampling the model. To solve the NP-Hard question as EDAs searching optimum network structure, a new Maximum Entropy Estimation of Distribution...
Unsolicited commercial email, also known as spam, has been a major problem on the Internet. In this paper a well known multiobjective evolutionary Algorithm, NSGA-II, is first time used for spam e-mail filtering. NSGA-II is adapted to use Genetic Programming components to achieve a set of filtering rules with different profiles.
In this paper, we present a novel evolutionary algorithm for dynamic risk grading of major hazards, which can be called DRGEA for short. And we detail the construction theory of DRGEA from many aspects such as individual encoding, evolutionary operators, fitness function and so forth. In the numerical experiment, DRGEA is used to solve a practical problem about dynamic risk grading of major hazards...
Spatial clustering with obstacles constraints (SCOC) has been a new topic in spatial data mining (SDM).In this paper, we propose an advanced Particle swarm optimization (PSO) and differential evolution (DE) method for SCOC. In the process of doing so,we first developed a novel spatial obstructed distance using PSO-DV(particle swarm optimization with differentially perturbed Velocity) based on grid...
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