求解柔性作业车间调度的混合粒子群算法

将粒子群算法运用于求解柔性作业车间调度问题,采用基于轮盘赌的编码方法以及基于邻域互换的局部搜索方法。通过两个不同规模算例的试验计算,与基于粒子位置取整的编码方法进行对比分析,说明了轮盘赌编码方法求解柔性作业车间调度问题的有效性。且采用该编码方法的混合粒子群算法在求解柔性作业车间调度问题时具有更好的求解性能。     

求解高维复杂优化问题的改进人工蜂群算法

为了提高人工蜂群算法求解高维复杂优化问题的能力,提出一种改进人工蜂群算法（artificial bee colony algorithm with attractor,BAABC）。在观察蜂阶段,BAABC算法摒弃轮盘赌选择策略,并通过引进吸引子改变观察蜂的搜索方式。首先,全局最优解波动产生吸引子。然后,观察蜂以吸引子为中心等比例收缩,共同开发同一区域,从而提高了算法的开发能力。实验结果表明,BAABC开发能力显著增强。关于迭代次数和时间,收敛速度都明显提高。在解决高维复杂优化问题方面,BAABC算法优势明显。值得一提的是,BAABC算法的收敛效果与问题维数无关,具有很好的鲁棒性。     

A particle swarm optimization based power dispatch algorithm with roulette wheel re-distribution mechanism for equality constraint

In this paper, a particle swarm optimization (PSO)-based power dispatch algorithm is proposed to deal with the energy management problem of the hybrid generation system (HGS). For conventional PSO method, the search space is only defined by inequality constraints. However, as for power dispatch problems, it is vital to maintain power balance, which can be represented as an equality constraint. To address this issue, a roulette wheel re-distribution mechanism is proposed. With this re-distribution mechanism, unbalanced power can be reallocated to more superior element and the searching diversity can be preserved. In addition, the effect of depth of discharge on the life cycle of the battery bank is also taken into account by developing a penalty mechanism. The proposed method is then applied to a HGS consisting of photovoltaic array, wind turbine, microturbine, battery banks, utility grid and residential load. To validate the effectiveness and correctness of the proposed method, simulation results for a whole day will also be provided. Comparing with three other power dispatching methods, the proposed method can achieve the lowest accumulated cost.     

Rare events probabilities estimation by “ Russian Roulette and Splitting ” simulation technique

An advanced Monte Carlo Simulation (MCS) technique—namely, “Russian Roulette and Splitting” (RR & S) technique is applied for the reliability assessment of mechanical systems under stochastic excitations. The basic features of the algorithm are described and discussed. As a numerical example the technique is used for the numerical solution of the first passage problem in the low probability range. Results are compared with available solutions, obtained by another variance reduction technique—“Double and Clump”(D & C) procedure.     

遗传选择算子的比较与研究

在改进的基本遗传算法的实验基础上,通过分析传统的基本选择算子的理论及其优缺点,提出了能够产生较好收敛速度的三种选择方法：基于上限的确定式采样、基于切断的轮盘赌选择以及无回放最大值选择法,通过实验证明其在收敛性和收敛速度上都有很大的改善,为一些需要更快速求到最优解的应用问题提供了更好的选择策略。     

优选策略的自适应蚁狮优化算法

针对基本蚁狮优化算法收敛速度较慢、易陷入局部极值、高维求解精度较低等缺点,提出具有自适应边界、优选轮盘赌和动态比例系数的改进蚁狮算法.在蚂蚁围绕蚁狮游走的过程中引入自适应边界机制,增加蚂蚁种群活跃性,防止算法陷入局部极值.轮盘赌选择蚁狮过程中加入优选轮盘赌策略,在保持蚁狮个体多样性的同时加快算法收敛速度.在蚂蚁位置更新公式中加入动态比例系数,提高算法前期的探索能力和后期的开发能力.理论分析证明文中算法的时间复杂度与基本算法相同.针对16个不同特征标准测试函数,在多个维度上的优化仿真实验测试结果表明,文中算法具有较好的可行性,寻优精度和收敛速度均有明显提升,受维度变化影响很小,高维求解能力更强、更稳定.     

一种非随机生成聚合组播路由转发表的算法

随着组播技术的应用,基于组播源地址和组播组地址进行二元组表项存储的组播路由转发表将呈爆炸式膨胀,内存消耗随之急剧增加,最终将成为组播路由转发的瓶颈之一.将组播路由转发表进行无类域间路由聚合成为一种有效的解决组播路由转发表爆炸式膨胀的一种方式.如何获取数据集是聚合组播路由表研究课题中,必然要解决的问题.由于组播路由转发表的聚合目前尚处在研究中,很难在网络上获取具有一定代表性的聚合组播路由转发表,而高性能路由算法的设计和实现与实际路由表的结构有很大关系.根据组播主干网组播IP地址分布的特性和规律,采取赌轮选择算法,非随机生成聚合组播路由转发表的方法,为仿真组播路由转发表和研究组播路由提供了依据.目前,应用聚合组播路由表算法的研究已取得了理想效果.