A New Ant Colony Optimization Method Considering Intensification and Diversification
A New Ant Colony Optimization Method Considering Intensification and Diversification
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DOI：
10.1007/978-3-642-44927-7_33
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发表时间：
2013-12
期刊：
影响因子：
--
通讯作者：
Mitsuru Haga;Shohei Kato
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文献类型：
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作者：
Mitsuru Haga;Shohei Kato
蚁群优化（ACO）是一种受蚂蚁觅食行为启发的元启发式算法，由于其简单性和高质量，是解决旅行商问题（TSP）的最著名的群体智能算法之一。在本文中，我们将提出一种名为 ASwide 的基于 ACO 的算法，该算法在信息素更新公式中添加了简单但强大的因素。为了检查我们算法的效率，我们做了几次计算机实验，并确认与其他方法相比，ASwide 可以稳定地生成可接受的解决方案。
Ant colony optimization (ACO) is a meta-heuristic algorithm inspired by foraging behavior of ants and is one of the most well known swarm intelligence algorithms for solving the Traveling Salesman Problem (TSP) because of its simpleness and quality. In this paper we will propose an ACO based algorithm called ASwide that adds simple but powerful factors in the pheromone updating formula. To check the efficiency of our algorithm we did several computer experiments and confirmed that ASwide generates an acceptable solution stably compared with other methods.