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.
With the development of mobile Internet technology and smart mobile devices, campus path navigation as a new trend have taken more attention. In this paper, we propose a new method based on quantum ant colony algorithm for campus path navigation. Quantum evolution algorithm has high effectiveness for solving combinational optimization problem. We combine ant colony algorithm with quantum evolution...
The search time of traditional ant colony Algorithm (ACA) is too long, and it tends to trap in local optimizations. In this paper, a fidelity-based ACA with Q-learning is presented to solve above-mentioned problem and applied for control of quantum system. In the fidelity-based ACA with Q-learning, fidelity is used in heuristic function, which can help the system converge to the optimal solution....
The Maximum Clique is the most compact cohesive subgroup in Social Network. Finding the maximum clique in the Social Network has become an important aspect of social network analysis, such as privacy protection, citation and co-citation analysis, cohesive subgroup analysis et al. With the development of big data, the mass of nodes in the graph and complexity of analysis set a higher requirement for...
To overcome the slow convergence and local optimum of ant colony algorithm, the cloud model theory is adopted to regulate reasonably the randomness of the ant colony algorithm. In this paper, several adaptive strategies are proposed for the parameters of the ant colony algorithm and the cloud model, and for the optimum path determination. Meanwhile, the evaluation algorithm of pheromone distribution...
In order to overcome the drawbacks of clonal genetic and ant clony algorithm, this paper presents a hybrid algorithm. First, using the feature of the genetic algorithm of random searching, coding efficiency, we can get high formation initial pheromone distribution of ant colony algorithm. Then, using the feature of the ant clony algorithm of the parallelism positive feedback mechanism, global convergence...
To solve the problem that the ant colony algorithm is easy to fall into local optimal solutions in solving the shortest path problem, improvements on the classical ant colony algorithm are provided in three aspects. Firstly, direction guiding is utilized in the initial pheromone concentration to speed up the initial convergence; secondly, the idea of pheromone redistribution is added to the pheromone...
Genetic algorithm has strong global search ability and robustness, but can not use the feedback of system and easy to do a lot of unnecessary redundancy iteration in the latter, resulting in the decline of convergence rate. Ant colony algorithm has the good characteristic of feedback, but due to lacking of initial pheromone, solving speed is slow. A method of adaptive dynamic integration is presented...
The traditional ant colony algorithm is based on the positive feedback mechanism. In essence, this guidance is conducive to the convergence of the algorithm but is not conducive to the diversity of the search. In order to shorten the length of the path of the optimization, this paper proposes an improved ant colony algorithm to improve search diversity. The algorithm, the positive feedback, the inverse...
Femtocell is an effective technology to improve the system performance. In this paper, we address the problem of sub-channels allocation in OFDMA two-tier femtocell networks. Our objective is to maximize the rate sum of multiple femtocells with consideration of cross-tier interference between macrocell and multiple femtocells. A resource optimization approach based on Ant Colony Optimization Algorithm...
It is difficult to determine optimal combination parameter which can make the solving performance of ant colony algorithm work better, owing to the bulkiness of parameter space and relevance among parameters. Until now, it has not owned perfect theoretical basis and been obtained mostly by repeated tests. Based on these problems, the paper finds a better combination parameter by balancing exploration...
Ant colony algorithm has been successfully applied to the Traveling Salesman Problem (TSP). But it has some disadvantages, such as easily plunging into local minimum, slow convergence speed and so on. In order to find the optimal path accurately and rapidly, an improved ant colony algorithm is proposed. The improved algorithm strengthens the consideration of the common information to induce ant colony...
An improved ant colony algorithm is proposed in this paper for Traveling Salesman Problems (TSPs). In the process of searching, the ants are more sensitive to the optimal path because the inverse of distance among cities is chosen as the heuristic information, while a candidate list is used to limit the number of candidate city. The method of local and global dynamic phenomenon update is used in order...
An ant colony algorithm using endpoint approximation is proposed for robot path planning under a unknown and static environment. In this algorithm the model of robot's workspace is established with grid method and fold-back iterating is used to search the aims. A heuristic factor based on the most pheromone in a moving direction range and a goal guiding function is used during the searching process...
To improve PSO, differential evolution (DEA) and ant colony strategy are involved into PSO algorithm, and new PSO(DAPSO) is presented. Handling the current optimal positions of particles with differential evolution, the detecting and exploitation ability of both PSO and DEA are utilized effectively, and some potential evolution directions are constructed for each particle in PSO, at the same time...
Distribution network optimization reconfiguration has important significance on improving distribution network operation. Ant colony algorithm is a common method in distribution network optimization reconfiguration. However, as there is the problem of slow convergence speed and local optimum, the development of ant colony algorithm is restricted in distribution network optimization. To solve the problems,...
Ant colony algorithm is a new algorithm of heuristic bionic calculation. Now, it has been widely applied in many fields of combinatorial optimization. This paper elaborates the basic principle and mathematical model of typical ant colony algorithm for solving the traveling salesman problem, and analyzes impact of the optimal parameters to the performance of algorithm. Based on its shortages, an improved...
This article elaborates the principle of ant colony algorithm of path planning for mobile robot in the first part, and explains that the interaction process of ant colony algorithm is a Markov process. Then the convergence property of ant colony algorithm is analyzed, and the methods to improve the convergence of ant colony algorithm are put forward. Finally, the effectiveness and feasibility of the...
Planning of the mobile robot is one of the core research areas which is complex, binding and non-linear. Ant colony algorithm is an intelligent optimization algorithm developed in recent years. Aiming at the problems of the ant colony algorithm such as slow convergence speed and long computation cycle, in order to improve the efficiency of route planning, proposed using improved ant colony algorithm...
As an intelligent algorithm with the mechanism of positive feedback, the ant colony algorithm is useful in solving the optimal problem. Web service selection is the foundation of the Web service composition which is one of the most important ways to satisfy the users' personalized requirements. Firstly, analyzed the problem of Web service selection based on expounding the basic principle of ant colony...
Ant Colony Algorithm (ACA) and Generation Algorithm (GA) are two bionic optimization algorithm, they are also two powerful and effective algorithms for solving the combination optimization problems, moreover they all were successfully used in traveling salesman problem (TSP) . This paper syncretizes two algorithms, meanwhile, a new syncretic method is put forward. The simulation results show that...
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.