Research on an improved optimization algorithm based on ant colony to solve WBC scanning routing problem

To solve white blood cell scanning routing problem, an improved optimization algorithm based on ant colony algorithm was proposed. The shortest equivalent time was selected as evaluating function. Pheromone updating rule and convergence strategy were added as well. Four algorithms were applied to the same WBC image frame and series of WBC image frames. The experimental results prove the effectiveness and excellence of the improved algorithm.

[1]  Marco Dorigo,et al.  Ant system: optimization by a colony of cooperating agents , 1996, IEEE Trans. Syst. Man Cybern. Part B.

[2]  Li Wenwei,et al.  The Research and Application on Improved Intelligence Optimization Algorithm Based on Knowledge Base , 2012, 2012 International Conference on Computer Science and Electronics Engineering.

[3]  Xuanjing Shen,et al.  An adaptive ant colony algorithm based on common information for solving the Traveling Salesman Problem , 2012, 2012 International Conference on Systems and Informatics (ICSAI2012).

[4]  Gao Hai-chang Reviews of the Meta-heuristic Algorithms for TSP , 2006 .

[5]  Mario Plebani,et al.  Automated blood cell counts: state of the art. , 2008, American journal of clinical pathology.

[6]  Zhiguo Liu,et al.  An Improved Ant Colony Optimization Algorithm Based on Pheromone Backtracking , 2011, 2011 14th IEEE International Conference on Computational Science and Engineering.

[7]  Yuzhen Pi,et al.  An Improvement to the Coordination Method of Ant Colony Algorithm , 2012, 2012 International Conference on Computer Distributed Control and Intelligent Environmental Monitoring.