The well-known ant colony optimization meta-heuristic is applied to design a new command to line-of-sight guidance law. In this regard, the lately developed continuous ant colony system is used to optimize the parameters of a pre-constructed fuzzy sliding mode controller. The performance of the resulting guidance law is evaluated at different engagement scenarios.

Both the clonal selection algorithm (CSA) and the ant colony optimization (ACO) are inspired by natural phenomena and are effective tools for solving complex problems. CSA can exploit and explore the solution space parallely and effectively. However, it can not use enough environment feedback information and thus has to do a large redundancy repeat during search. On the other hand, ACO is based...

The Vehicle Routing Problem (VRP) is an important management problem in the field of physical distribution and logistics. Good vehicle routing can not only increase the profit of logistics but also make logistics management more scientific. The Capacitated Vehicle Routing Problem (CVRP) constrained by the capacity of a vehicle is the extension of VRP. Our research applies a two-phase algorithm ...

In this paper we propose an extension of classification algorithm based on ant colony algorithms to handle continuous valued attributes using the concepts of fuzzy logic. The ant colony algorithms transform continuous attributes into nominal attributes by creating clenched discrete intervals. This may lead to false predictions of the target attribute, especially if the attribute value history i...

This paper overviews origin and some applications of ant system of optimization. Ants live in colonies. The colony can be regarded as a multiagent organization where each agent performs independently as governed by goal of colony survival.. On observing the behavior of ants, Ant-Algorithm was proposed. The ant algorithms have been extensively studied by European researchers. These algorithms ha...

Since the introduction of Ant Colony Optimization (ACO) technique in 1992, the algorithm starts to gain popularity due to its attractive features. However, several shortcomings such as slow convergence and stagnation motivate many researchers to stop further implementation of ACO. Therefore, in order to overcome these drawbacks, ACO is proposed to be combined with Differential Evolution (DE) an...

This paper explores the task scheduling algorithm for cloud computing on the basis of Particle Swarm Optimization (PSO). Based on task scheduling problems of the cloud computing, first of all, this paper detailed introduction to cloud computing, task scheduling of cloud computing, particle swarm optimization algorithm and ant colony optimization algorithm. On this basis of the above, task sched...

Ant colony optimization(ACO), which is one of the intelligential optimization algorithm, has been widely used to solve combinational optimization problems. Deceptive problems have been considered difficult for ant colony optimization. It was believed that ACO will fail to converge to global optima of deceptive problems. This paper proves that the first order deceptive problem of ant colony algo...