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.
While using genetic algorithm to solve constrained optimization problems, some of its shortcomings appear such as difficulty in obtaining feasible individuals in many strong constraint conditions and poor local search ability. In this paper, an algorithmic thought of constraints scattering is presented to divide the complete constraints of a problem into several sub-populations for processing, which...
Considering the limitation of standard genetic algorithm such as premature convergence and low convergence speed, an improved genetic algorithm based on adaptive evolution in dual population (DPAGA) is proposed. In this algorithm, the new population produced by selecting operation is regarded as the main population. The population composed by the individuals washed out by selecting operation is regarded...
In order to avoid slow-convergence and local convergence of simple genetic algorithm (SGA) for intelligent test paper generation, a kind of improved genetic algorithm (IGA)has been proposed in this paper. This algorithm uses unceasing elimination of similar individual method to quickly enlarge the search space and to stabilize the individual diversity of the group. Experiment results show that the...
Distribution system optimal planning has vital significance, but there isn't efficient and practical algorithm at Traditional genetic algorithm has a poor expressive power for complicated problem because of the restriction of its norm mode, which limits the application fields of genetic algorithm. This paper adapts the idea of “Ethogenetics” reference, and presents a new type of genetic algorithm...
The paper introduces the principle of genetic algorithm and analyses the selection of parameters of genetic algorithm. By an example, the paper researches the different effect of each parameter. Such as, the size of the population (M), the probability of crossover (Pc) and the probability of mutation (Pm). By the experimentation and simulation, The paper brings forward a general method for selection...
Tree encodings of programs are well known for their representative power and are used very often in Genetic Programming. In this paper we experiment with a new data structure, named straight line program (slp), to represent computer programs. The main features of this structure are described and new recombination operators for GP related to slp's are introduced. Experiments have been performed on...
In this paper we present an application of the grouping genetic algorithm to the problem of assigning students to laboratory groups in university courses. This problem includes an important constraint of capacity, due to laboratories usually have a maximum number of equips or computers available, so the number of total students in a group is constrained to be equal or less than the capacity of the...
In this paper we propose a new approach for applying genetic programming to lossless data compression based on combining well-known lossless compression algorithms. The file to be compressed is divided into chunks of a predefined length, and GP is asked to find the best possible compression algorithm for each chunk in such a way to minimise the total length of the compressed file. This technique is...
Link enhancement problem is a combinatorial optimization problem, and genetic algorithm is suitable to solve the combinatorial optimization problem. Commonly, the genetic algorithms are adopt one dimension code, this paper adopt the dual-structure code and adaptive probabilities of crossover and mutation to solve the link enhancement problem. In the simulation experiment, we compare the performance...
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.