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.
In the field of Evolutionary Computation (EC), many algorithms have been proposed to enhance the optimisation search performance in NP-Hard problems. Recently, EC research trends have focused on memetic algorithms that combine local and global optimisation search. One of the state-of-the-art memetic EC methods named Bacterial Memetic Algorithm (BMA) has given good optimisation results. In this paper,...
A novel clustering algorithm called Immune Memetic Clustering Algorithm (IMCA) is proposed in the paper. IMCA combines Immune Clone Selection and Memetic algorithm; Two populations are used in the evolutionary process. Clone reproduction and selection, Memetic mutation, crossover, individual learning and selection are adopted to evolve the two populations. After watershed proceeding, extracting the...
In this paper, a novel immune algorithm with dynamic memetic Cauchy mutation (DMCMIA) for multi-objective optimization is proposed. The idea of memetics is incorporated into the mutation process and a dynamic memetic Cauchy mutation (DMCM) operator is developed. The DMCM operator combines global exploration and local refinement efficiently, which adopts a generation-dependent parameter to guarantee...
The goal of the path planning problem is to determine an optimal collision-free path between a start and a target point for a mobile robot in an environment surrounded by obstacles. This problem belongs to the group of hard optimization problems which can be approached by modern optimization techniques such as evolutionary algorithms. In this paper the bacterial memetic algorithm is proposed for path...
Evolutionary methods and in particular Bacterial Memetic Algorithms are widely adopted means of population based metaheuristics, which have the ability to perform robust search on a discrete problem space. These methods are categorized as black-box search heuristics and tend to be quite good at finding generally good approximate solutions on certain problem domains such as the Traveling Salesman Problem...
In order to study the function approximation performance of Fuzzy Neural Networks built up from fuzzy J-K flip-flop neurons a new learning algorithm, the Three Step Bacterial Memetic Algorithm is proposed. Hybrid evolutionary methods that combine genetic type algorithms with “classic” local search have been applied to perform efficient global search. This novel version of the Bacterial Memetic Algorithm...
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.