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1.
The paper presents a new solution of inverse displacement analysis of the general six degree-of-freedom serial robot. The inverse displacement analysis of the general serial robot is transformed into a minimization problem and then the optimization method is adopted to solve the nonlinear least squares problem with the analytic form of new Jacobian matrix. In this way, joint variables of the general serial robot can be searched out quickly under the desired precision when positions of the three non-collinear end effector points are given. Compared with the general Newton iterative method, the proposed algorithm can search out the solution when the robot is at the singular configuration and the initial configuration used in the optimization method may also be the singular configuration. So the convergence domain is bigger than that of the general Newton iterative method. Another advantage of the proposed algorithm is that positions of the three non-collinear end effector points are usually much easier to be measured than the orientation of the end effector. The inverse displacement analysis of the general 6R (six-revolute-joint) serial robot is illustrated as an example and the simulation results verify the efficiency of the proposed algorithm. Because the three non-collinear points can be selected at random, the method can be applied to any other types of serial robots.  相似文献   

2.
A new approach is proposed to improve the general identification algorithm of multidimensional systems using wavelet networks. The general algorithm involves mapping vector input into its norm to avoid problem of dimensionality in construction multidimensional wavelet basis functions. Thus, the basis functions are spherically symmetric without direction selectivity. In order to restore the direction selectivity, the improved approach weights the input variables before mapping it into a scalar form. The weights can be obtained using universal optimization algorithms. Generally, only local optimal weights are obtained. Even so, performance of identification can be improved.  相似文献   

3.
In this paper, a new method named as the gradually descent method was proposed to solve the discrete global optimization problem. With the aid of an auxiliary function, this method enables to convert the problem of finding one discrete minimizer of the objective function f to that of finding another at each cycle. The auxiliary function can ensure that a point, except a prescribed point, is not its integer stationary point if the value of objective function at the point is greater than the scalar which is chosen properly. This property leads to a better minimizer of f found more easily by some classical local search methods. The computational results show that this algorithm is quite efficient and reliable for solving nonlinear integer programming problems.  相似文献   

4.
As a basic mathematical structure,the system of inequalities over symmetric cones and its solution can provide an effective method for solving the startup problem of interior point method which is used to solve many optimization problems.In this paper,a non-interior continuation algorithm is proposed for solving the system of inequalities under the order induced by a symmetric cone.It is shown that the proposed algorithm is globally convergent and well-defined.Moreover,it can start from any point and only needs to solve one system of linear equations at most at each iteration.Under suitable assumptions,global linear and local quadratic convergence is established with Euclidean Jordan algebras.Numerical results indicate that the algorithm is efficient.The systems of random linear inequalities were tested over the second-order cones with sizes of 10,100,,1 000 respectively and the problems of each size were generated randomly for 10 times.The average iterative numbers show that the proposed algorithm can generate a solution at one step for solving the given linear class of problems with random initializations.It seems possible that the continuation algorithm can solve larger scale systems of linear inequalities over the secondorder cones quickly.Moreover,a system of nonlinear inequalities was also tested over Cartesian product of two simple second-order cones,and numerical results indicate that the proposed algorithm can deal with the nonlinear cases.  相似文献   

5.
The standard particle swarm optimization (PSO) algorithm is a novel evolutionary algorithm in which each particle studies its own previous best solution and the group's previous best solutions to optimization problems. One problem in PSO is its tendency of trapping into local optima. In this paper, a multi-swarm technique based on fast particle swarm optimization(FPSO) algorithm is proposed by introducing crossover operation. FPSO is global search algorithm which can prevent PSO from trapping into local optima in light of Cauchy mutation. Though it can get high optimizing precision, the convergence rate is not satisfactory. FMSO can not only find satisfying solutions, but also speed up the search.  相似文献   

6.
This paper presents the forward displacement analysis of an 8-PSS (prismatic-spherical-spherical) redundant parallel manipulator whose moving platform is linked to the base platform by eight kinemtic chains consisting of a PSS joint and a strut with fixed length. A general approximation algorithm is used to solve the problem. To avoid the extraction of root in the approximation process, the forward displacement analysis of the 8-PSS redundant parallel manipulator is transformed into another equivalent problem on the assumption that the strut is extensible while the slider is fixed. The problem is solved by a modified approximation algorithm which predicates that the manipulator will move along a pose vector to reduce the difference between the desired configuration and an instantaneous one, and the best movement should be with minimum norm and least quadratic sum. The characteristic of this modified algorithm is that its convergence domain is larger than that of the general approximation algorithm. Simulation results show that the modelified algorithm is general and can be used for the forward displacement analysis of the redundant parallel manipulator actuated by a revolute joint.  相似文献   

7.
In this paper,we propose a novel adjustable multiple cross-hexagonal search(AMCHS) algorithm for fast block motion estimation. It employs adjustable multiple cross search patterns(AMCSP) in the first step and then uses half-way-skip and half-way-stop technique to determine whether to employ two hexagonal search patterns(HSPs) subsequently. The AMCSP can be used to find small motion vectors efficiently while the HSPs can be used to find large ones accurately to ensure prediction quality. Simulation results showed that our proposed AMCHS achieves faster search speed,and provides better distortion performance than other popular fast search algorithms,such as CDS and CDHS.  相似文献   

8.
The attribute reduction algorithms of decision table based on discernible matrix are required to construct discernible matrix, which reduces efficiency of algorithms. In this paper, the relationship between attribute discernible matrix and its discernibility is first established for general information systems. Based on the idea that the equivalent discernible matrix has a same attribute reduction, existing matrices are modified and a formula of attribute discernibility associated with algebraic reduction for decision table is proposed. A heuristic attribute reduction algorithm based on attribute discernibility is presented. Experimental results indicate that the algorithm can more easily explore an optimal or sub-optimal reduction, and is efficient.  相似文献   

9.
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   

10.
This paper presents a new genetic algorithm for the resource-constrained project scheduling problem(RCPSP).The algorithm employs a standardized random key(SRK) vector representation with an additional gene that determines whether the serial or parallel schedule generation scheme(SGS) is to be used as the decoding procedure.The iterative forward-backward improvement as the local search procedure is applied upon all generated solutions to schedule the project three times and obtain an SRK vector,which is rese...  相似文献   

11.
针对八数码问题的求解,给出了深度优先搜索、广度优先搜索和启发式搜索(譬如A*算法)之间的算法比较,通过实验验证各种算法并得出结论:在通常情况下,采用启发式搜索算法来进行状态空间的搜索更为方便、高效。  相似文献   

12.
给出一种结合梯度法和正交遗传算法的混合算法。实验表明,它通过对问题的解空间交替进行全局和局部搜索,能更有效地求解函数优化问题。  相似文献   

13.
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   

14.
Web语义搜索结果排序一直是搜索引擎的主要研究课题之一。但是目前通用的算法例如OntoKhoj排序算法和AKTiveRank排序算法的排序结果并不理想,主要原因是排序思路比较片面,公式中的系数很难确定。针对这一问题,我们结合了OntoKhoj算法和AKTiveRank的优势,提出了O&A算法,并使用遗传算法对O&A中的系数进行了优化。实验表明,O&A算法的排序结果要明显优于OntoKhoj排序算法和AKTiveRank排序算法。  相似文献   

15.
根据DNA杂交测序的特点,设计了一个改进的最大最小蚂蚁算法.首先,对问题进行预处理,将其转化为有约束的非对称旅行商问题;然后,对状态转移规则和全局更新规则进行改进,并运用变量邻域搜索思想,设计了一种简单高效的局部搜索技术.最后,采用后处理技术来解决长度约束问题.实验结果表明:该算法提高了DNA杂交测序的求解精度.  相似文献   

16.
k均值算法是一个常用的局部搜索算法,它的主要缺陷是容易陷入局部极小,并且该局部极小解与全局最优解往往有很大的偏差。本文提出一个基于K-均值的迭代局部搜索文档聚类算法。该算法以k均值算法所得到的解作为初始解,从该初始解开始作局部搜索。在搜索过程中接受部分劣解。当解无法改进时,算法对所得到的局部极小解做适当强度的扰动后进行下一次的迭代,以跳出局部极小,从而拓展了搜索的范围。实验结果表明该算法对文档数据集聚类的正确性迭99%以上。  相似文献   

17.
基于粒子群算法的可靠性优化   总被引:2,自引:0,他引:2  
系统可靠性优化已被证明是一个NP完全问题,不存在精确的求解方法。人们构造了大量的启发式算法,如遗传算法(GA),蚁群算法(ACO),模拟退火算法(SA)等。针对各种算法所存在的早熟收敛,易陷入局部极值点的缺点,提出了将粒子群算法(particle swarm optimization,PSO)用于求解可靠性问题。给出了基于粒子群算法的可靠性优化求解策略,根据数学模型,详细讨论了求解步骤,最后给出了实验仿真结果。结果表明该算法具有较强的局部搜索能力,同时也有更高的搜索效率,与其它方法相比,该算法能够找到更优解,验证了该算法的可行性和有效性。  相似文献   

18.
INTRODUCTION The vehicle routing problem (VRP), which was first introduced by Dantzig and Ramser (1959), is a well-known combinatorial optimization problem in the field of service operations management and logis- tics. The capacitated vehicle routing problem (CVRP) is an NP-hard problem for simultaneously determining the routes for several vehicles from a central depot to a set of customers, and then return to the depot without exceeding the capacity constraints of each vehicle. In pr…  相似文献   

19.
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   

20.
基于改进遗传算法的GSM基站选址问题研究   总被引:1,自引:0,他引:1  
本文首先对于罚函数遗传算法构造了合适的适应度计算方式,其次将适当的修补算子加入修补遗传算法中,保证修补的随机性和有效性;然后在两者的交叉、变异操作之后都加入进化突变算子,增强了他们的局部搜索能力;最后针对不同规模的基站选址问题,分别采用加入进化突变前后的罚函数遗传算法和修补遗传算法进行仿真,结果验证加入进化突变的修补遗传算法在求解大规模的基站选址问题时效率最高。  相似文献   

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