In this paper we introduce a biobjective ant colony algorithm for constructing low cost overlay routing networks. The ant colony algorithm is distributed and adaptive in finding shortest paths from source to destination nodes while also constructing a low cost overlay routing network. Additionally, we define a cost model for overlay network construction that includes network traffic demands. Th...

Traditional method of test paper generation is time-consuming, low efficient and low success. In order to improve the success rate of test paper, the paper puts forward an ant colony algorithm of automatic sets method. First, a mathematical model of constraint is built according to the requires of papers, and by using the ant colony algorithm, the optimal solution of grouping is obtained. Simul...

-In this paper a hybrid variant of meta-heuristic algorithm ant colony optimization (ACO) is used. Approximate solutions to quadratic assignment problem have been proved very efficient. Different variants of ant colony optimization have been applied to QAP. But in this paper a hybrid approach is proposed which is combination of Ant system and Max-Min Ant system to take benefits of both the meth...

With the development of aerospace engineering, the space on-orbit servicing has been brought more attention to many scholars. Obstacle avoidance planning of space manipulator end-effector also attracts increasing attention. This problem is complex due to the existence of obstacles. Therefore, it is essential to avoid obstacles in order to improve planning of space manipulator end-effector. In t...

This paper introduces the wireless sensor network routing protocol and its security, and introduces the main several kinds of routing protocols, including the data centric routing protocol, hierarchical routing protocols and location-based routing protocol, finally according to the analysis of routing protocol common attack method. Ant colony algorithm is a distributed parallel algorithm. A sin...

Ant colony algorithms are a class of metaheuristics which are inspired from the behaviour of real ants. The original idea consisted in simulating the stigmergic communication, therefore these algorithms are considered as a form of adaptive memory programming. A new formalization was proposed for the design of ant colony algorithms, introducing the biological notions of heterarchy and communicat...

Enlightened by the behaviors of gregarious ant colonies, an artificial ant movement (AM) model and an adaptive ant clustering (AAC) algorithm for this model are presented. In the algorithm, each ant is treated as an agent to represent a data object. In the AM model, each ant has two states: sleeping state and active state. In the algorithm AAC, the ant’s state is controlled by both a function o...

clustering is a widespread data analysis and data mining technique in many fields of study such as engineering, medicine, biology and the like. the aim of clustering is to collect data points. in this paper, a cultural algorithm (ca) is presented to optimize partition with n objects into k clusters. the ca is one of the effective methods for searching into the problem space in order to find a n...

The ant colony optimization (ACO) algorithms are multi-agent systems in which the behaviour of each ant is inspired by the foraging behaviour of real ants to solve optimization problem. This paper presents the ACO based algorithm to find global minimum. Algorithm is based on that each ant searches only around the best solution of the previous iteration. This algorithm was experimented on test p...

Among the many bio-inspired techniques, ant clustering algorithms have received special attention, especially because they still require much investigation to improve performance, stability and other key features that would make such algorithms mature tools for data mining. Clustering with swarm-based algorithms is emerging as an alternative to more conventional clustering methods, such as e.g....