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1.
对多配送中心车辆路径问题进行描述,并建立该问题的数学模型,设计了求解多配送中心车辆路径问题的两阶段算法。第一阶段把多配送中心车辆路径问题转化成单配送中心车辆路径问题,提出基于边界客户分配法的转化策略;第二阶段对单配送中心车辆路径问题进行求解,采用禁忌搜索算法进行优化求解,最后表明算法的有效性和可行性。  相似文献   

2.
针对标准遗传算法在解决带时间窗的车辆路径问题(VRPTW)时存在早熟收敛和易陷入局部极值点的特点,引入遗传算法与禁忌搜索结合的混合算法,同时对杂交算子进行了改进.算法既具有遗传算法的全局性和并行性,又具有禁忌搜索算法的爬山能力.实验表明,改进的混合算法具有计算效率高、收敛速度快等特点,是一种有效的方法.  相似文献   

3.
The permutation flowshop scheduling problem (PFSP) is one of the most well-known and well-studied production scheduling problems with strong industrial background. This paper presents a new hybrid optimization algorithm which combines the strong global search ability of artificial immune system (AIS) with a strong local search ability of extremal optimization (EO) algorithm. The proposed algorithm is applied to a set of benchmark problems with a makespan criterion. Performance of the algorithm is evaluated. Comparison results indicate that this new method is an effective and competitive approach to the PFSP.  相似文献   

4.
应用于液压集成块优化的一种混合遗传-退火算法   总被引:1,自引:0,他引:1  
This paper establishes a mathematical model of multi-objective optimization with behavior constraints in solid space based on the problem of optimal design of hydraulic manifold blocks (HMB). Due to the limitation of its local search ability of genetic algorithm (GA) in solving a massive combinatorial optimization problem, simulated annealing (SA) is combined, the multi-parameter concatenated coding is adopted, and the memory function is added. Thus a hybrid genetic-simulated annealing with memory function is formed. Examples show that the modified algorithm can improve the local search ability in the solution space, and the solution quality.  相似文献   

5.
通过对梯度法与模拟退火算法优缺点的分析,提出了一种梯度退火新型混合全局优化算法。该算法利用梯度法的快速寻优特性得到某一局部极值,然后采用模拟退火算法的全局搜索寻优能力跳出该局部极值,经过反复混合迭代最终获得全局最优解。仿真实验表明,该新型混合优化算法显著提高了求解全局优化问题的计算效率。  相似文献   

6.
基于混合遗传算法的关系型数据库多连接查询优化   总被引:1,自引:0,他引:1  
倪小剑 《鄂州大学学报》2005,12(6):16-18,28
该文分析了关系型数据库的查询优化问题,针对多连接查询提出将遗传算法和爬山法结合,从而构造了关系型数据库多连接查询优化问题的混合遗传算法,并进行了实验计算。结果表明,用混合遗传算法解决多连接查询优化问题,可以发挥遗传算法和爬山法的不同优势,从而得到较满意的查询优化性能。  相似文献   

7.
研究了一类新的车辆路线问题(VRP)——整合逆向物流的多车辆路线问题(MVRPRL).该问题的特点是客户可以同时取货和发货,而且客户发货量是在路线安排前是不确定的.首先用三角模糊数表示客户发货量,建立了基于模糊置信度理论的多目标模型;然后设计了基于模拟的改进禁忌算法来求解该模型:用模拟的方法计算路线失败值,在路线搜索中采用路线内部改善和路线间改善两类邻域操作,而且采用了重起策略.计算结果表明该方法优于传统的扫描算法,整合逆向物流的运输费用比正逆向分别运输之和减少了43%.  相似文献   

8.
针对NP-完全的无等待流水作业调度问题,改变传统求解调度序列目标函数的模式,分析并证明启发式算法基本算子的目标增量性质,通过目标函数变化量判断新解的优劣,大大降低算法所需计算时间.提出将变化邻域搜索(VNS)作为一种局部搜索机制混合入遗传算法的智能算法IGA求解所考虑的问题,根据问题特点构造ISG算法产生初始种群中的一个个体,设计基于期望值的个体选择机制和进化过程交叉算子ILCS.采用110个经典Benchmark实例,将所提出的IGA算法与传统遗传算法以及求解该问题目前最好的2种算法进行比较,实验结果表明IGA算法在略有耗时的情况下,性能上明显优于其他3种算法、  相似文献   

9.
Optimal strategy of searching FPD weights scanning matrix using GA-PSO   总被引:1,自引:0,他引:1  
This paper discusses a kind of optimal method used for searching flat panel display (FPD) scanning matrix. The method adopts bionic algorithm: genetic algorithm (GA) and particle swarm optimization (PSO) algorithm. The method using single GA is more time-consuming, and the search efficiency is low in later evolution; the PSO algorithm is easily falling into the local optimal solution and appears the premature convergent phenomenon. Hence, a hybrid approach of GAPSO is found to optimize the search for high grayscale weights scanning matrix. Finally in the acceptable time, it finds a weight scanning matrix (WSM) of 256 gray scales with Matlab, whose scanning efficiency reaches 94.73% and the linearity is very good.  相似文献   

10.
We extended an improved version of the discrete particle swarm optimization (DPSO) algorithm proposed by Liao et al.(2007) to solve the dynamic facility layout problem (DFLP). A computational study was performed with the existing heuristic algorithms, including the dynamic programming (DP), genetic algorithm (GA), simulated annealing (SA), hybrid ant system (HAS), hybrid simulated annealing (SA-EG), hybrid genetic algorithms (NLGA and CONGA). The proposed DPSO algorithm, SA, HAS, GA, DP, SA-EG, NLGA, and CONGA obtained the best solutions for 33, 24, 20, 10, 12, 20, 5, and 2 of the 48 problems from (Balakrishnan and Cheng, 2000), respectively. These results show that the DPSO is very effective in dealing with the DFLP. The extended DPSO also has very good computational efficiency when the problem size increases.  相似文献   

11.
Genetic algorithms (GAs) employ the evolutionary process of Darwin's nature selection theory to find the solutions of optimization problems. In this paper, an implementation of genetic algorithm is put forward to solve a classical transportation problem, namely the Hitchcock's Transportation Problem (HTP), and the GA is improved to search for all optimal solutions and identify them automatically. The algorithm is coded with C and validated by numerical examples. The computational results show that the algorithm is efficient for solving the Hitchcock's transportation problem.  相似文献   

12.
This paper presents a new method based on an immune-tabu hybrid algorithm to solve the thermal unit commitment (TUC) problem in power plant optimization. The mathematical model of the TUC problem is established by analyzing the generating units in modem power plants. A novel immune-tabu hybrid algorithm is proposed to solve this complex problem. In the algorithm, the objective function of the TUC problem is considered as an antigen and the solutions are considered as antibodies, which are determined by the affinity computation. The code length of an antibody is shortened by encoding the continuous operating time, and the optimum searching speed is improved. Each feasible individual in the immune algorithm (IA) is used as the initial solution of the tabu search (TS) algorithm after certain generations of IA iteration. As examples, the proposed method has been applied to several thermal unit systems for a period of 24 h. The computation results demonstrate the good global optimum searching performance of the proposed immune-tabu hybrid algorithm. The presented algorithm can also be used to solve other optimization problems in fields such as the chemical industry and the power industry.  相似文献   

13.
为克服粒子群算法在处理复杂高维问题时易陷入局部最优及寻优精度低等缺陷,提出一种融合 Rosenbrock 搜索法的混合粒子群算法。首先,利用 Tent 混沌序列进行种群初始化;其次,采用去速度项的简化粒子群公式提高收敛速度并对个体极值加入扰动,增强粒子种群多样性;最后,当全局最优个体更新停滞时,利用Rosenbrock 搜索法对全局最优个体进行局部搜索,提高解的精度。利用 8 个常用基准测试函数分别对 30 维和50 维问题进行实验,证实该算法可寻到病态函数 Rosenbrock 全局最优值,且比其它 7 个函数的寻优精度提高10-2 数量级。实验证明该算法收敛速度快,解的精度高,全局搜索能力强,寻优能力明显提高。  相似文献   

14.
分析了无线传感器网络的特点及各种路由协议的优缺点,将改进的遗传算法方案应用到无线传感器网络分簇路由优化问题中,在满足传感器网络约束条件的基础上智能地计算出最佳路由,使通信距离最小化。模拟实验的结果表明,本文提出的算法方案在解决无线传感器网络路由优化问题中具有良好的综合求解能力。  相似文献   

15.
尽管蚁群优化算法(ACO)在优化计算中已得到了很多应用,但在进行大规模优化时,其收敛时间过长仍是应用该算法的一个瓶颈.为了确保资源利用完成时间最小化和完成用户指定的最终期限延迟最小化,找到一个优化的调度方法,在计算网格中针对资源分配和调度提出了基于蚁群优化和遗传操作的混合方法.  相似文献   

16.
使用调和均值的KHM聚类算法,不像KH聚类算法,具有对初始值不敏感的优点。但它作为一个基于中心聚类算法,难以摆脱早熟收敛的问题。为了克服KHM算法的不足,本文提出结合ABC和KHM的ABC—KHM混合聚类算法。在混合算法中,聚类行为可以分为两个阶段:全局搜索的ABC聚类阶段和局部求精的KHM聚类阶段。通过仿真实验,并与KHM聚类算法进行了比较,结果表明:ABC-KHM混合聚类算法,不仅对聚类初始值不敏感,而且具有较快的聚类速度、良好的全局聚类效果,是一个不错的聚类算法。  相似文献   

17.
We present a new algorithm for nesting problems. Many equally spaced points are set on a sheet, and a piece is moved to one of the points and rotated by an angle. Both the point and the rotation angle constitute the packing attitude of the piece. We propose a new algorithm named HAPE (Heuristic Algorithm based on the principle of minimum total Potential Energy) to find the optimal packing attitude at which the piece has the lowest center of gravity. In addition, a new technique for polygon overlap testing is proposed which avoids the time-consuming calculation of no-fit-polygon (NFP). The detailed implementation of HAPE is presented and two computational experiments are described. The first experiment is based on a real industrial problem and the second on 11 published benchmark problems. Using a hill-climbing (HC) search method, the proposed algorithm performs well in comparison with other published solutions.  相似文献   

18.
连续型Hopfield神经网络(CHNN)可用于优化计算,但其会遭遇较复杂的参数辨识问题.为了较好地解决这一问题,将擅长全局搜索的蚁群-粒子群混合算法用于对系统参数的最优化选取.再将此混合算法与CHNN有机结合,更好地解决参数辨识问题,且能有效避免CHNN在应用过程中陷入局部最优解.最后,将理论结果应用于求解TSP问题来验证其有效性.  相似文献   

19.
The K-means algorithm is one of the most popular techniques in clustering. Nevertheless, the performance of the K- means algorithm depends highly on initial cluster centers and converges to local minima. This paper proposes a hybrid evolutionary programming based clustering algorithm, called PSO-SA, by combining particle swarm optimization (PSO) and simulated annealing (SA). The basic idea is to search around the global solution by SA and to increase the information exchange among particles using a mutation operator to escape local optima. Three datasets, Iris, Wisconsin Breast Cancer, and Ripley's Glass, have been considered to show the effectiveness of the proposed clustering algorithm in providing optimal clusters. The simulation results show that the PSO-SA clustering algorithm not only has a better response but also converges more quickly than the K-means, PSO, and SA algorithms.  相似文献   

20.
为了实现农产品物流配送车辆路径的合理优化,降低物流配送成本和提高消费者满意度,提出一种基于灰狼优化算法的多目标农产品物流配送车辆路径优化模型。选择物流配送成本最低和路径最短为目标函数,将灰狼位置编码为车辆编号和车辆路径顺序,通过灰狼优化算法实现多目标农产品物流配送车辆路径的最优规划。研究结果表明,与PSO和GA相比,在行驶里程和平均行驶成本方面,GWO的成本最低且行驶里程最少。  相似文献   

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