共查询到19条相似文献,搜索用时 154 毫秒
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混合模拟植物生长算法在包装件配送中的应用 总被引:1,自引:1,他引:0
目的针对改进模拟植物生长算法(IPGSA)容易陷入局部最优解及其算法运行时间较长,提出混合模拟植物生长算法(HPGSA)来求解带时间窗车辆调度问题(VSPTW)。方法在IPGSA基础上,提出求解包装件物流配送中VSPTW的混合模拟植物生长算法(HPGSA)。改进IPGSA初始调度方案的构造方式,设计求解VSPTW的C-W算法用于构造HPGSA的初始调度方案;改进IPGSA的邻域搜索算子,选择插入搜索算子和互换搜索算子对HPGSA进行邻域搜索;对18个不同规模的Solomon算例进行仿真测试。结果相对于其他智能算法,HPGSA具有更好的求解性能,能够保证VSPTW对求解算法的要求。结论 HPGSA的全局优化能力、稳定性和运行速度均优于IPGSA、遗传算法、蚁群算法和禁忌搜索算法。 相似文献
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借鉴禁忌搜索的思想改进了人工免疫网络算法(aiNet),提出一种禁忌人工免疫网络算法(TS-aiNet).在算法中引入禁忌表,禁忌在网络迭代中亲和力不再增加的细胞,通过特赦准则赦免一些被禁忌的优良状态;增加记忆表,保存成熟的记忆细胞;重新定义高斯变异方式,保证多样化的搜索.利用Markov链分析了该算法的全局收敛性,通过对典型系统的仿真实验分析了该算法的性能,并与克隆选择算法和opt-aiNet算法进行了比较,最终将改进的算法运用到红外与可见光图像配准中,像素级配准精度可以达到0.5像素.实验结果表明,该算法在多模态搜索空间中具有更好的全局收敛性、稳定性和发现极值点能力,能够克服早熟现象,提高图像配准的速度和精度,是一种有效的全局优化方法. 相似文献
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《中国新技术新产品》2016,(7)
从数学角度分析,配电网无功优化是一个非线性、多变量、多约束的混合规划问题。粒子群优化搜索算法被广泛应用于求解配电网无功优化问题。由于粒子群算法粒子群在进化过程易趋向同一化,失去多样性,从而使算法陷入局部最优解。本文在分析配电网无功优化的特性基础上,提出一种改进的紧融合禁忌搜索-粒子群算法用于配电网无功优化问题的求解。通过将禁忌搜索功能融合到粒子历史最优解和全局最优解寻优过程中,避免了粒子群算法寻优过程中出现的局部最优问题,从而提高粒子群算法的全局搜索能力。通过IEEE14节点系统的仿真计算结果表明,改进的算法能取得良好的效果。 相似文献
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面向多处理器SoC设计的低功耗软硬件划分 总被引:1,自引:0,他引:1
提出了解决多处理器SoC的低功耗软硬件划分问题的方法--基于神经网络的禁忌搜索算法.其基本思想是:真实的生物神经元具有抑制重复激活的阻尼特性,这与禁忌搜索对重复搜索加以限制相类似,因此设计具有阻尼特性的神经网络实现禁忌搜索算法,受阻尼特性抑制的神经元对应禁忌活动.由于神经网络复杂的动态特性和禁忌搜索优秀的全局搜索能力,该算法能够有效地跳出局部最优解.对真实任务图的实验表明,与遗传算法相比,该算法不但具有搜索速度上的优势,而且所得到的绝大部分软硬件划分方案有更低的系统功耗. 相似文献
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基于连续函数优化的禁忌搜索算法 总被引:1,自引:0,他引:1
提出了一种连续禁忌搜索算法,用于求解连续函数优化问题.邻域规则及禁忌规则是禁忌搜索算法的核心,针对连续函数解空间的连续性,提出了一种邻域分割法来进行邻域搜索,并对禁忌规则进行了设计.通过经典函数测试可以看出,禁忌搜索算法在连续函数优化问题中显示出很强的"爬山"能力,优化结果与实际最优值非常接近,是一种有效的全局优化算法. 相似文献
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耦合局部最优法作为一种新型的优化技术,既具有高效的搜索速度又具有全局搜索能力.然而,对于大规模优化问题,该方法容易陷入局部最优;另外,梯度信息在该项技术中起着重要作用,而对于复杂问题往往不能得到精确的梯度信息,从而使得该算法的全局搜索能力下降.本文分别从初始种群的确定、变步长搜索、自调节种群三方面对原算法进行了改进,提出了自适应耦合局部最优法,使之具备解决多变量复杂优化问题的能力.通过两个测试函数验证了改进算法比原有算法更易于得到全局最优解并保持较高的计算效率.最后,采用一个试验算例验证了自适应耦合局部最优法的有效性. 相似文献
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包装物回收物流中的车辆路径优化问题 总被引:2,自引:2,他引:0
目的提高遗传算法(GA)求解包装物回收车辆路径优化问题的性能。方法通过对传统GA算法的改进,提出混合蜂群遗传算法(HBGA)。首先改进传统GA算法的初始种群生成方式,设计初始种群混合生成算子;其次,提出最大保留交叉算子,对优秀子路径进行保护;然后,在上述改进的基础上引入蜜蜂进化机制,用以保证种群多样性和优秀个体特征信息的利用程度;最后,对标准算例集进行仿真测试。结果与传统GA算法相比,HBGA算法在全局寻优能力、算法稳定性和运行速度方面均有所改善。HBGA算法的全局寻优能力和算法稳定性均优于粒子群算法(PSO)、蚁群算法(ACO)和禁忌搜索算法(TS),但运行速度稍慢于TS算法。结论对传统GA算法的改进是合理的,且HBGA算法整体求解性能优于PSO算法、ACO算法和TS算法。 相似文献
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针对薄壁件超声铣削加工时产生的颤振严重影响工件质量,加剧刀具磨损的问题,搭建了颤振图像监测系统,利用卷积神经网络(CNN)进行颤振图像辨识,综合运用趋磁细菌算法(MB)、爬山算法(HC)和禁忌算法(TS)的优点,改进MB算法进行超参数优化,提出了一种基于改进趋磁细菌卷积神经网络(IMB-CNN)的薄壁件超声铣削颤振辨识方法。首先,通过MB算法进行全局搜索,再以最优解为初始点,通过HC算法进行邻域搜索,避免了MB算法在最优解附近的振荡;同时,通过禁忌列表跳过已搜索的节点,减小计算规模,加快计算效率;最后,将获得的最优超参数用于CNN,实现颤振图像的精确辨识。与其他方法相比,该方法实现了97.69%的识别率,判断时间为363ms,能有效地进行颤振监测,且整体性能较优。 相似文献
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Adil Baykasoglu 《International journal for numerical methods in engineering》2006,65(3):406-424
One of the first multiple objective versions of the tabu search (TS) algorithm is proposed by the author. The idea of applying TS to multiple objective optimization is inspired from its solution structure. TS works with more than one solution (neighbourhood solutions) at a time and this situation gives the opportunity to evaluate multiple objectives simultaneously in one run. The selection and updating stages are modified to enable the original TS algorithm to work with more than one objective. In this paper, the multiple objective tabu search (MOTS) algorithm is applied to multiple objective non‐linear optimization problems with continuous variables using a simple neighbourhood strategy. The algorithm is applied to four mechanical components design problems. The results are compared with several other solution techniques including multiple objective genetic algorithms. It is observed that MOTS is able to find better and much wider spread of solutions than the reported ones. Copyright © 2005 John Wiley & Sons, Ltd. 相似文献
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P. SIARRY G. BERTHIAU 《International journal for numerical methods in engineering》1997,40(13):2449-2457
Tabu Search (TS) is a stochastic global optimization procedure which proved efficient to solve various combinatorial optimization problems. However, very few works deal with its application to global minimization of functions depending on continuous variables. The aim of this paper is to propose an adaptation of TS to the optimization of continuous functions, and to study the influence of the main algorithm parameters on the convergence towards the optimum. In particular, the application of TS to function optimization involves the definition of the current solution neighbourhood and the management of the tabu list. The efficiency of TS applied to continuous global optimization has been tested in detail by using classical multimodal functions for which minima are known. © 1997 by John Wiley & Sons, Ltd. 相似文献
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目的为了提高蝙蝠算法(BA)求解包装废弃物逆向物流问题的性能。方法在标准BA算法的基础上提出混合蝙蝠算法(HBA)。首先,构建新型蝙蝠表达式,使BA算法适用于包装废弃物逆向物流问题的求解。其次,引入自适应惯性权重,改造蝙蝠速度更新公式;然后,引入粒子群算法(PSO),对每次迭代中任一随机蝙蝠进行粒子群操作;最后,利用HBA算法对企业实例和标准算例进行仿真测试。结果企业最优回收距离为776.63 km。与遗传算法(GA)、蚁群算法(ACO)和禁忌搜索算法(TS)相比,HBA算法能够求得已知最优解的标准算例个数最多为6个,求得最好解与已知最优解的平均误差最小为8.58%,平均运行时间最短为4.39s。结论 HBA算法的全局寻优能力、稳定性和运行速度均优于GA算法、ACO算法和TS算法。 相似文献
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遗传算法在接近全局最优解时,存在搜索速度变慢、过早收敛、个体的多样性减少很快、甚至陷入局部最优解等问题。通过在遗传算法中引入模拟退火因子、混沌因子和多样性测度因子,在很大程度上克服了原有遗传算法的早熟、局部搜索能力差的缺点。同时,又能发挥原有遗传算法的强大的全局搜索能力,保证了改进后的混合遗传算法能较好地收敛于其全局最优值。 相似文献
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With the expansion of the application scope of social computing problems,
many path problems in real life have evolved from pure path optimization problems to
social computing problems that take into account various social attributes, cultures, and
the emotional needs of customers. The actual soft time window vehicle routing problem,
speeding up the response of customer needs, improving distribution efficiency, and
reducing operating costs is the focus of current social computing problems. Therefore,
designing fast and effective algorithms to solve this problem has certain theoretical and
practical significance. In this paper, considering the time delay problem of customer
demand, the compensation problem is given, and the mathematical model of vehicle path
problem with soft time window is given. This paper proposes a hybrid tabu search (TS) &
scatter search (SS) algorithm for vehicle routing problem with soft time windows
(VRPSTW), which mainly embeds the TS dynamic tabu mechanism into the SS
algorithm framework. TS uses the scattering of SS to avoid the dependence on the quality
of the initial solution, and SS uses the climbing ability of TS improves the ability of
optimizing, so that the quality of search for the optimal solution can be significantly
improved. The hybrid algorithm is still based on the basic framework of SS. In particular,
TS is mainly used for solution improvement and combination to generate new solutions.
In the solution process, both the quality and the dispersion of the solution are considered.
A simulation experiments verify the influence of the number of vehicles and maximum
value of tabu length on solution, parameters’ control over the degree of convergence, and
the influence of the number of diverse solutions on algorithm performance. Based on the
determined parameters, simulation experiment is carried out in this paper to further prove
the algorithm feasibility and effectiveness. The results of this paper provide further ideas
for solving vehicle routing problems with time windows and improving the efficiency of
vehicle routing problems and have strong applicability. 相似文献
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Machines and automated guided vehicles (AGVs) scheduling problems are two essential issues that need to be addressed for the efficiency of the overall production system. The purpose of this paper is to study the simultaneous scheduling problem of machines and AGVs in a flexible manufacturing system (FMS) since the global optimum cannot be reached by considering each of them individually. In this paper, a mixed integer linear programming (MILP) model is developed with the objective of makespan minimisation. The MILP model consists of the following two constraint sets: machines and AGVs scheduling sub-problems. As both sub-problems are known to be NP-hard, a heuristic algorithm based on tabu search (TS) is proposed to get optimal or near to optimal solution for large-size problems within reasonable computation time. The proposed algorithm includes a novel two-dimensional solution representation and the generation of two neighbour solutions, which are alternately and iteratively applied to improve solutions. Moreover, an improved lower bound calculation method is introduced for the large-size problems. Computational results show the superior performance of the TS algorithm for the simultaneous scheduling problem. 相似文献
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It has been well established that to find an optimal or near-optimal solution to job shop scheduling problems (JSSPs), which are NP-hard, one needs to harness different features of many techniques, such as genetic algorithms (GAs) and tabu search (TS). In this paper, we report usage of such a framework which exploits the diversified global search and the intensified local search capabilities of GA and TS, respectively. The system takes its input directly from the process information in contrast to having a problem-specific input format, making it versatile in dealing with different JSSP. This framework has been successfully implemented to solve industrial JSSPs. In this paper, we evaluate its suitability by applying it on a set of well-known job shop benchmark problems. The results have been variable. The system did find optimal solutions for moderately hard benchmark problems (40 out of 43 problems tested). This performance is similar to, and in some cases better than, comparable systems, which also establishes the versatility of the system. However for the harder benchmark problems it had difficulty in finding a new improved solution. We analyse the possible reasons for such a performance. 相似文献
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针对约束优化问题,提出一种适于约束优化的增强差异演化算法(enhanced differential evolution algorithm for constrained optimization, ECDE).在约束处理上采用不可行域与可行域更新规则的方法,避免了传统的惩罚函数方法中对惩罚因子的设置,使算法的实现变得简单.改进了DE算法的变异操作,对选择的3个父代个体进行操作遍历,产生6个候选解,取适应值最优的为变异操作的解,大大改善了算法的稳定性、鲁棒性和搜索性能.通过4个测试函数和1个设计实例仿真,表明所提出的算法具有较快的收敛速度和较好的稳定性和鲁棒性. 相似文献