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The Improvement and Application of the Ant Colony Algorithm

Author: WangZhiJie
Tutor: QuanHuiYun
School: Hunan Normal University
Course: Computer Software and Theory
Keywords: Degree constrained minimum spanning tree problem Ant Colony Algorithm Maximum Clique Problem Combinatorial optimization problems
CLC: TP301.6
Type: Master's thesis
Year: 2009
Downloads: 210
Quote: 9
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Abstract


The ant colony algorithm is a by simulating real ants foraging principle developed novel bionic intelligent optimization algorithm, with positive feedback , parallel and enlightening search . As one of the important branch of computational intelligence and swarm intelligence , the ant colony algorithm in the ascendant , came under scrutiny. The ant colony algorithm development background , content , methods and performance are described in detail , a more in-depth study of the algorithm itself , own flaws and unknown characteristics of the ant colony algorithm , the improvement program and simulation experiments . The main research results are as follows: Algorithm for AS DCMST problem convergence speed is slow and easy to converge to a local optimum phenomenon , this paper proposes a new improved algorithm UDA- ACS . The algorithm uses the basic idea of the ACS algorithm , and introduces a different amount of the initial information given for the different length paths , the dynamic negative feedback mechanism to adjust the amount of change of the pheromone , the dynamic appropriately increased visibility influence on the ant path selection mechanism effectively inhibit converge to a local optimum and slow convergence phenomenon , and to improve the quality and speed of the algorithm search . Simulation results show that the improved algorithm show a certain superiority . Addressed the maximum clique problem ( MCP ) , the paper proposes a new improved the algorithm ACO - BVD . The algorithm on the basis of the Vertex-AC , the global pheromone update mechanism based on the vertex degree inspired shows information to help to guide the choice of the next vertex pheromone local pheromone update mechanism to assist co - complete vertex pheromone profile , introducing a pseudo - random proportional rule adjusted ants \pheromone updating , and improve the operating efficiency of the algorithm and the quality of the solution . Using MCP benchmark instances , superiority in performance of the algorithm by comparing the experimental validation .

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > General issues > Theories, methods > Algorithm Theory
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