融合黑寡妇优化与记忆引导的混合蚁群算法求解旅行商问题

高 宏(辽宁科技大学计算机科学与技术学院,中国)
李 迎春(辽宁科技大学计算机科学与技术学院,中国)

DOI: http://dx.doi.org/10.12349/iser.v7i3.9479

Article ID: 9479

摘要


针对旅行商问题求解中传统的蚁群算法收敛速度慢、容易陷入局部最优的缺陷,本文提出一种融合黑寡妇优化算法(BWO)和记忆引导机制(MGA)的混合蚁群算法(MGA-BWO-ACO)。该算法构建“预热-记忆-搜索”三位一体协同机制:BWO预热生成高质量初始解提升收敛速度,记忆库动态积累搜索经验引导蚂蚁选择路径,蚁群算法进行全局搜索,并集成局部搜索与自适应重启策略。数据实验结果表明,该算法显著提升了全局搜索能力与收敛速度,优化了求解的质量与效率,具有广泛应用潜力。

关键词


旅行商问题;寡妇优化算法;蚁群算法;记忆引导机制;混合算法

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参考


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