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 this paper, a discrete fruit fly optimization algorithm (DFOA) is proposed for solving the capacitated vehicle routing problem (CVRP). Firstly, a two-part discrete array is presented to represent the solution. Secondly, the initialization based on K-means is proposed to take full use of the location information of the customers. The customers in each cluster are allocated to one vehicle. Meanwhile,...
Multimodal optimization (MMO) is the problem of finding many or all global and local optima. In recent years many efficient nature-inspired techniques (based on ES, PSO, DE and others) have been proposed for real-valued problems. Many real-world problems contain variables of many different types, including integer, rank, binary and others. In this case, the weakest representation (namely binary representation)...
This paper presents a differential evolutionary clustering approach to solve the optimization of the dimension weights in subspace, which is referred to as Soft Subspace Clustering Using Differential Evolutionary Algorithm (DESSC). The classical clustering methods can handle the low-dimensional rather than the high-dimensional data due to the curse of dimensionality. In addition, many subspace clustering...
Krill herd (KH) is a new recent nature inspired stochastic search algorithm. The fitness function of this algorithm depends upon the minimum distance of each krill from food and the algorithms aims to increase the population diversity around the food cluster. In this paper, the improved krill herd algorithm is employed to solve the optimization problems. The neighborhood distance concept is introduced...
The well-known K-means algorithm has been successfully applied to many practical clustering problems, but it has some drawbacks such as local optimal convergence and sensitivity to initial points. Particle swarm optimization algorithm (PSO) is one of the swarm intelligent algorithms, it is applied in solving global optimization problems. An integration of enhanced PSO and K-means algorithm is becoming...
In Multi-objective Optimization the goal is to present a set of Pareto-optimal solutions to the decision maker (DM). One out of these solutions is then chosen according to the DM preferences. Given that the DM has some general idea of what type of solution is preferred, a more efficient optimization could be run. This can be accomplished by letting the optimization algorithm make use of this preference...
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.