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Alternative TitleImproved Ant Colony Algorithmfor Solving Continuous Space Optimization Problems
段海滨; 马冠军; 王道波; 于秀芬; 北京8701信箱
Source Publication系统仿真学报
Keyword蚁群算法 信息素 正反馈 连续空间优化
Other AbstractAnt colony algorithm is a novel category of bionic meta-heuristic algorithm, and parallel computation and positive feedback mechanism are adopted in this algorithm. The ant colony algorithm has strong robustness and easy to combine with other methods in optimization. Although the ant colony algorithm for the heuristic solution of discrete space optimization problems enjoys a rapidly growing popularity, but few are reported for the heuristic solution of continuous space optimization problems. Based on the introduction of the mechanism and mathematical model of basic ant colony algorithm, an improved ant colony algorithm for solving continuous space optimization problems was proposed.The solution vector of continuous space optimization problem was decomposed into finite grids. Meanwhile, the cost function related to the transition probability was constructed.In order to enhance the global convergence performance of the improved ant colony algorithm,meeting search strategy was adopted in the improved ant colony algorithm, and the range of possible pheromone trails on each solution component was limited to a maximum-minimum interval. The numerical simulation results demonstrate that the improved ant colony algorithm can find better global solution for continuous space optimization problems than the adaptive ant colony algorithm proposed in the literature [11],and this new algorithm presents a feasible and effective way to solve various continuous space optimization problems.
Indexed ByCSCD
Funding Project中国科学院空间科学与应用研究中心
Citation statistics
Cited Times:36[CSCD]   [CSCD Record]
Document Type期刊论文
Corresponding Author北京8701信箱
Recommended Citation
GB/T 7714
段海滨,马冠军,王道波,等. 一种求解连续空间优化问题的改进蚁群算法[J]. 系统仿真学报,2007,19(5):974-977.
APA 段海滨,马冠军,王道波,于秀芬,&北京8701信箱.(2007).一种求解连续空间优化问题的改进蚁群算法.系统仿真学报,19(5),974-977.
MLA 段海滨,et al."一种求解连续空间优化问题的改进蚁群算法".系统仿真学报 19.5(2007):974-977.
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