Liu Liqiang, Dai Yuntao, Gao Jinyu
College of Automation, Harbin Engineering University, 145 Nantong Street, Heilongjiang 150001, China.
College of Science, Harbin Engineering University, 145 Nantong Street, Heilongjiang 150001, China.
ScientificWorldJournal. 2014;2014:428539. doi: 10.1155/2014/428539. Epub 2014 May 11.
Ant colony optimization algorithm for continuous domains is a major research direction for ant colony optimization algorithm. In this paper, we propose a distribution model of ant colony foraging, through analysis of the relationship between the position distribution and food source in the process of ant colony foraging. We design a continuous domain optimization algorithm based on the model and give the form of solution for the algorithm, the distribution model of pheromone, the update rules of ant colony position, and the processing method of constraint condition. Algorithm performance against a set of test trials was unconstrained optimization test functions and a set of optimization test functions, and test results of other algorithms are compared and analyzed to verify the correctness and effectiveness of the proposed algorithm.
连续域蚁群优化算法是蚁群优化算法的一个主要研究方向。本文通过分析蚁群觅食过程中位置分布与食物源之间的关系，提出了一种蚁群觅食分布模型。我们基于该模型设计了一种连续域优化算法，并给出了算法的解的形式、信息素分布模型、蚁群位置更新规则以及约束条件的处理方法。针对一组无约束优化测试函数和一组优化测试函数对算法性能进行了测试，并与其他算法的测试结果进行了比较和分析，以验证所提算法的正确性和有效性。
