The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Sexual reproduction plays an important role in evolution. However, in classic genetic algorithms(GAs), the evolutionary process is only implemented on an unisexual population. Although some sexual selection schemes for GAs have been proposed, only limited studies are focused on detailed mechanisms in sexual selection. In this paper, we focus on the modeling of some significant components in sexual...
In practice, two key problems have been found in genetic algorithm (GA), one is premature convergence and the other is weak local search ability. In this paper, a new hybrid genetic algorithm based on chaos and particle swarm optimization (PSO) is proposed to solve the two problems above. The basic principle is that chaotic search mechanism and PSO mutation are added into the framework of simple genetic...
This paper presents an improved gene expression programming (GEP) algorithm based on multi-phenotype chromosomes (MPC-GEP). The populations in MPC-GEP are composed of chromosomes with multiple phenotypes. Each multi-gene chromosome corresponds to multiple expression trees. The new algorithm can find the optimal individual in less time than traditional GEP. Finally, experiments on the new algorithm...
Traveling salesman problem (TSP) is a typical NP-complete problem, of which the search space increases with the number of cities. Genetic algorithm (GA) is an efficient optimization algorithm characterized with explicit parallelism and robustness, applicable to TSP. In this paper, we compare the performance of the existing GAs in searching the solution for TSP and find a superior combination of crossover...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.