Self-adaptive Ant Colony Algorithm Research Articles

Ant Colony Algorithm Dynamically Adjust the Parameters Based on Chaos Theory

Ant colony algorithm as an intelligent bionic optimization algorithm, Because of its use of positive feedback mechanism, the result will be prone to premature, stagnation and slow speed of solving the problem etc. For this shortcoming is proposed based on chaos theory adaptive dynamic parameters ant colony algorithm (PDSACA Dynamic Parameters Self-adaptive Ant Colony Algorithm).In the process of the dynamic algorithm solving, introducing chaotic disturbance technique, the parameters of the algorithm design of dynamic changes to affect the algorithm quality and global parameters are adjusted adaptively to improve the global search capability. By using the TSPLABs reference example to test the algorithm. Experimental results show that the convergence of the algorithm, robustness and efficiency have been improved to Compare with the basic ant colony algorithm.

Path Planning and Replanning for Intelligent Robot Based on Improved Ant Colony Algorithm

The effectiveness of path planning and path replanning for intelligent robot using improved ant colony algorithm is explored in this paper. For the purpose of avoiding falling into local optimum and preventing iterative stagnant, this paper describes a new algorithm named stochastic self-adaptive ant colony algorithm to improve the basic ant colony algorithm. Based on the improved ant colony algorithm, the approaches of path planning and path replanning are presented in this paper. Aiming at improving the speed of the algorithm and simplifying the objective function of traditional path planning, this paper presents a principle of eliminating the path nodes .Finally, some constrast emulators are designed.The simulation results proves that the improved ant colony algorithm has strong adaptability in intelligent robots path path planning and replanning.

Research on the Optimization of Transportation Routing Problem of Warehouse Material Based on Self-Adaptive Ant Colony Algorithm

Ant colony algorithm is an intelligent optimization algorithm derives heuristically from simulating ants to seek food, the paper firstly creates the VRP model of warehouse material transportation,self-adaptive ant colony algorithm is used for solving the model. This paper gives some measures to improve the Ant colony algorithm in the procedure to seek the solution.At last, the experimental results based on MATLAB show that this algorithm is extremely effective to solve the optimal solutions of VRP. Its application in VRP has achieved good results.

The Research of Self-Adaptive Ant Colony Algorithm with Path Smoothing

The Research of Self-Adaptive Ant Colony Algorithm with Path Smoothing