An adaptive path selection method for delay testing

For verifying the correctness of a circuit, not only its logic function, but also its timing behavior must be considered. Although the path delay fault model can handle part of the weakness of the gate delay fault model, it also has inherent deficiencies. Since the number of paths in a logic circuit is tremendous, exhaustively testing each signal propagation path is prohibitive. To deal with the weakness of traditional delay test techniques, based on the path delay fault model, a new delay test approach including a new delay test output observation method and an adaptive path selection method is proposed in this work. The basic idea of the approach is to measure the signal transition time for each delay test, and more paths are selected for a second-stage test (if necessary) to ensure the timing behavior of the circuit under test. Experimental results obtained by computer simulation demonstrate that a more thorough test is really a need if many significantly late signal transitions are observed     

Detecting electrical shorts on printed circuit boards

Consider a printed circuit board with N signal paths in which k (not known a priori) paths are subjected to electrical shorts. A straight forward technique to detect all shorts is to test each pair of signal paths separately. This method needs (N² — N)/2 tests. In order to reduce the testing effort, manufacturers introduced a device that could test a group of signal paths against another group of signal paths. With the help of this device, a method with N + ((k² —k)/) tests needed was patented in 1982. In this paper, we present a new method that requires only O(k[log₂ N]) tests to achieve the same resolution using the same device.     

改进粒子群算法在农产品物流配送路径管理中的应用

目的 为了更加合理地进行车辆路径调度管理,提高粒子群求解车辆路径优化问题的性能。方法 提出了一种动态猴子跳跃机制的粒子群优化算法,它借助群体的动态分组,采用不同的动态惯性权重来提高算法的速度,引入猴子跳跃机制来保证全局收敛性。最后把改进算法应用到物流配送路径优化的2个实例中,同一环境下,改进算法搜寻到最优路径适应值、平均运算时间,以及求得最优解的成功次数,均优于标准粒子群优化算法。结果 结果表明,改进的算法能快速有效地确定物流配送路径。结论 改进粒子群优化算法不仅具有较快的寻优速度,而且也提高了算法的收敛性,保证了寻优质量,因此具有很大的应用价值。     

基于模糊聚类分析的家具零件成组研究

合理的零件分组是成组技术实施的关键因素之一,对山东省德州市某板式衣柜厂典型产品进行零件成组案例研究,通过生产流程分析,建立零件相似矩阵,利用传递闭包法求出等价矩阵,从而实现理性化的零件成组分类,进而通过Matlab的编程实现复杂零件系统的成组。结果表明：随着分组阈值的不断增加,分组数量随之增加,零件平均相似度也随分组阈值的不断增加而增加, 企业生产规模与选择的分组阈值、零件分组数量成反向关系,企业规模越小,分组数量应较小,从而实现组内零件较大批量的生产加工。     

一种基于点集自适应分组构建Voronoi图的并行算法

论文提出一种基于点集自适应分组构建Voronoi图的并行算法,其基本思路是采用二叉树分裂的方法将平面点集进行自适应分组,将各分组内的点集独立生成Voronoi图,称为Voronoi子图;提取所有分组内位于四边的边界点,对边界点集构建Voronoi 图,称为边界点Voronoi图;最后,针对每个边界点,提取其位于Voronoi子图和边界点Voronoi 图内所对应的两个多边形,进行Voronoi多边形的合并,最终实现子网的合并.考虑到算法耗时主要在分组点集的Voronoi图生成,而各分组的算法实现不受其他分组影响,采用并行计算技术加速分组点集的Voronoi图生成.理论分析和测试表明,该算法是一个效率较高的Voronoi图生成并行算法.     

Tool path generation via the multi-criteria optimisation for flat-end milling of sculptured surfaces

A method of generating optimal tool paths for sculptured surface machining with flat-end cutters is presented in this paper. The inclination and tilt angles, as well as the feed directions of the cutter at each cutter contact point on a machining path are optimised as a whole so that the machining width of the tool path can be as large as possible, and concerns such as smooth cutter motion, gouging avoidance, scallop height and machining widths overlap are also considered when calculating a path. A multi-criteria tool path optimisation model is introduced, and it is converted into a single objective optimisation with the weighted sum method. The Differential Evolution (DE) algorithm is suitable for solving this highly non-linear problem. However, the searching process of the DE algorithm may be trapped in local minima due to large number of design variables. Therefore, an algorithm combining the DE algorithm and the sequence linear programming algorithm is developed to solve this optimisation model. The proposed method is applied to two freeform surfaces to illustrate its effectiveness.     

An algorithm for locating short circuits among N signal paths usingK-port parallel short detector

To locate short circuits on a printed circuit board, a K-port parallel short detector can test K signal paths simultaneously. If the total number of signal paths N on a printed circuit board is larger than K, then we need to divide the testing process into multiple stages such that at most R signal paths are tested in each stage. In this paper, we design a parallel algorithm to locate all the short circuits among the N signal paths on a printed circuit board using a K-port parallel short detector where Ki's such that S_i contains at most K signal paths, and then it bisects S_i into two disjoint sets T_2i-1 and T_2i, (2) it locates all the short circuits in S_i for all i, and (3) it locates all the short circuits between S_i and S_j for all i≠j by testing T_2i-1 against T_2j-1, T_2i-1 against T_2j, T_2i against T_2j-1, and T _2i against T_2j     

An Efficient Algorithm for Global Path Optimization in MPLS Networks

This paper proposes an algorithm to solve the optimization of label switched paths (LSPs) in multiprotocol label switching (MPLS) networks. The underlying optimization problem in this task is the well-known unsplittable multicommodity flow problem equipped with practically relevant objective functions and specialized with hard technical requirements.The proposed heuristic algorithm is based on network flow theory. It incorporates iterative shortest path search and performs adaptive edge weight adjustments in order to successfully satisfy all the required traffic demands and to maximize user-defined objectives. The robust algorithm facilitates the incorporation of several strategic and optimization objectives and the fulfillment of certain hard technical requirements of the target problem domain as well. Novel features of the approach include a new adaptive path allocation/deallocation strategy based on the identification of bottleneck links, demand ordering and preprocessing phases, and a systematic path allocation control method.The efficiency of the method is empirically shown on randomly generated networks with practical sizes and topologies, and on a real-world IP (Internet Protocol) backbone network. The algorithm is able to successfully solve difficult problem instances comprising very large instances with 1000 nodes, 3500 edges and 999000 traffic demands. The computational tests demonstrate that the proposed approach can be efficiently applied to solve problem instances that embed MPLS specific hard technical requirements. Furthermore, it is shown that our algorithm offers significantly better performance than the straightforward adaptations of existing methods that were developed for related network optimization problems. Namely, our algorithm produces acceptable results quicker, it can solve problems that were not previously solvable, and it yields better results than the alternative methods. The extensive empirical tests demonstrate the combinatorial properties of the target problem and the performance aspects of the algorithm and its components as well.     

纤维铺放轨迹规划的两种方法及其比较研究

为了实现纤维铺放轨迹规划,本文提出了两种方法,即网格化方法和CAD软件的二次开发方法。针对网格化方法,提出了自由曲面的网格化方法和四边形网格铺放轨迹生成算法。针对CAD软件的二次开发方法,基于UG软件,提出了可变计算步长的初始轨迹计算方法、轨迹优化算法和丝束数量计算方法。以某型号的S形飞机进气道为参考模型,利用两种方法分别进行了轨迹规划。最后,对两种开发方法进行了比较研究,发现第二种方法相对于第一种方法具有功能强、开发周期短、与CAD软件的集成度高等优点,得出了其更适合铺放软件开发的结论。     

Constrained pseudo-Brownian motion and its application to image enhancement

Brownian motion is a random process that finds application in many fields, and its relation to certain color perception phenomena has recently been observed. On this ground, Marini and Rizzi developed a retinex algorithm based on Brownian motion paths. However, while their approach has several advantages and delivers interesting results, it has a high computational complexity. We propose an efficient algorithm that generates pseudo-Brownian paths with a very important constraint: we can guarantee a lower bound to the number of visits to each pixel, as well as its average. Despite these constraints, we show that the paths generated have certain statistical similarities to random walk and Brownian motion. Finally, we present a retinex implementation that exploits the paths generated with our algorithm, and we compare some images it generates with those obtained with the McCann99 and Frankle and McCann's algorithms (two multiscale retinex implementations that have a low computational complexity). We find that our approach causes fewer artifacts and tends to require a smaller number of pixel comparisons to achieve similar results, thus compensating for the slightly higher computational complexity.     

Comparison of the stress responses of an aluminum alloy tube to proportional and alternate axial and shear strain paths at room temperature

A servocontrolled axial-torsion mechanical testing machine and strain measurements on the uniform section of thin-walled tubes of the aluminum alloy 6061 T6 were used to examine a continuity argument put forth by Rivlin (1981). Displacement boundary conditions were enforced (strain control) during proportional paths and paths involving alternate axial and shear strain steps. In separate tests the number of steps was increased from two to ten, twenty and forty steps.As expected, the results show that the alloy obeys the continuity hypothesis although the ‘total strain path lengths’ for the proportional and the step tests are different. The inelastic strain path length (accumulated inelastic strain) of multistep tests approaches that of the proportional loading test as the number of steps increases. It has not been demonstrated that the stress response of the endochronic theory based on ‘total strain path length’ does not obey the continuity hypothesis. However, other examples are given which show that the predictions of this theory do not correspond to some typical metal deformation behavior.     

Double global optimum genetic algorithm–particle swarm optimization-based welding robot path planning

Spot-welding robots have a wide range of applications in manufacturing industries. There are usually many weld joints in a welding task, and a reasonable welding path to traverse these weld joints has a significant impact on welding efficiency. Traditional manual path planning techniques can handle a few weld joints effectively, but when the number of weld joints is large, it is difficult to obtain the optimal path. The traditional manual path planning method is also time consuming and inefficient, and cannot guarantee optimality. Double global optimum genetic algorithm–particle swarm optimization (GA-PSO) based on the GA and PSO algorithms is proposed to solve the welding robot path planning problem, where the shortest collision-free paths are used as the criteria to optimize the welding path. Besides algorithm effectiveness analysis and verification, the simulation results indicate that the algorithm has strong searching ability and practicality, and is suitable for welding robot path planning.     

Component grouping for GT applications—a fuzzy clustering approach with validity measure

The variety of the currently available component grouping methodologies and algorithms provide a good theoretical basis for implementing GT principles in cellular manufacturing environments. However, the practical application of the grouping approaches can be further enhanced through extensions to the widely used grouping algorithms and the development of criteria for partitioning components into an ‘optimum’ number of groups. Extensions to the fuzzy clustering algorithm and a definition of a new validity measure are proposed in this paper. These are aimed at improving the practical applicability of the fuzzy clustering approach for family formation in cellular manufacturing environments. Component partitioning is based upon assessing the compactness of components within a group and overlapping between the component groups. The developed grouping methodology is experimentally demonstrated using an industrial case study and several well known component grouping examples from the published literature.     

The entropic basis of collective behaviour

We identify a unique viewpoint on the collective behaviour of intelligent agents. We first develop a highly general abstract model for the possible future lives these agents may encounter as a result of their decisions. In the context of these possibilities, we show that the causal entropic principle, whereby agents follow behavioural rules that maximize their entropy over all paths through the future, predicts many of the observed features of social interactions among both human and animal groups. Our results indicate that agents are often able to maximize their future path entropy by remaining cohesive as a group and that this cohesion leads to collectively intelligent outcomes that depend strongly on the distribution of the number of possible future paths. We derive social interaction rules that are consistent with maximum entropy group behaviour for both discrete and continuous decision spaces. Our analysis further predicts that social interactions are likely to be fundamentally based on Weber''s law of response to proportional stimuli, supporting many studies that find a neurological basis for this stimulus–response mechanism and providing a novel basis for the common assumption of linearly additive ‘social forces’ in simulation studies of collective behaviour.     

基于遗传算法的AUV三维海底路径规划

研究AUV在三维海底地形环境中的路径规划问题。针对三维地形中路径的不同特点，将路径分为3种类型。设计了优化路径的遗传算法实现方案，所提出的惩罚函数及启发性知识的使用，使算法能灵活的得到具有不同特点的最优路径。仿真实验表明了该算法的可行性与可靠性，对AUV的安全航行具有重要的理论意义及应用参考价值。     

Dispersion in stellar interferometry: simultaneous optimization for delay tracking and visibility measurements

In long-baseline optical stellar interferometry, it is necessary to maintain optical path equality between the two arms of an interferometer in order to measure the fringe visibility. There will be errors in matching the optical paths because of a number of factors, and it is desirable to use an automatic system to monitor and correct such path errors. One type of system is a delay tracker, based on imaging of the channeled spectrum. The tracking algorithm is designed to maintain a fixed number of fringes, ideally linearly spaced, across the observed spectral band. This results in a constant optical path difference, which may be incompatible with the requirement of path equality for the measurement of fringe visibility. In a practical interferometer that uses an optical path-length compensator operating in air, there is a complication since air paths introduce differential dispersion. This dispersion can be compensated for by including dispersion correction. By modifying the operation of an appropriately designed dispersion corrector, we show that it is possible to make the optical path difference zero at the measurement wavelength and, at the same time, to produce linearly spaced channel fringes across the tracking band.     

Robust network coding against path failures

In this study, an approach for robust network coding is introduced for multicast in a directed acyclic network in the presence of network edge failures. The proposed designs aim at combating the resulting path failures, which result in interestingly scalable solutions. A robust network coding scheme (RNC1) is proposed that, devising a rate-path diversity trade-off for the receivers, attains the post-failure capacity of the network with high probability. The scheme is receiver based and can also be applied for correcting random erasures. Next, a rate-guaranteed robust network coding scheme (RNC2) is proposed. The code guarantees the maximum rate for a predetermined number of path failures. The scheme, of course, attains the refined Singleton bound for the edge failure model. A path failure may not necessarily reduce the network capacity, as the remaining intact edges within the network may still facilitate backup paths from the source to the sinks. We introduce RNC3 to employ such backup paths in addition to the original paths and guarantee multicast at a certain rate in the presence of all edge/path failure patterns that do not reduce the capacity below this rate. All the three proposed schemes for multicast are robust to a number of edge failures that may, in general, exceed the refined Singleton bound. Our analyses indicate that the design complexities and the required field sizes grow as a function of the number of network paths, as opposed to the number of network edges because of prior schemes.     

Efficient tool path planning for five-axis surface machining with a drum-taper cutter

This paper presents a new efficient approach to NC tool path generation for five-axis surface machining. First, an efficient cutter, named a drum-taper cutter, is proposed; its key dimension is determined to avoid gouging in surface machining according to the maximum curvature of the surface calculated with a genetic algorithm. Then, based on the drum-taper cutter, the tool paths are generated so that the scallop height formed by adjacent tool paths in machining is kept constant, and an improved algorithm for calculating the interval between tool paths is presented. Finally, an example of tool path generation with the above method for arbitrary surface impeller machining is conducted, and the results show that the presented method leads to a significant reduction in the total tool path length and is accompanied by a reduction in machining time.     

Formation of independent flow-line cells based on operation requirements and machine capabilities

In this paper we study the generalized grouping problem of cellular manufacturing. We propose an operation-sequence-based method for forming flow-line manufacturing cells. Process planning in the form of selection of the machine for each operation is included in the problem formulation. Input requirements include the set of operation requirements for each part type, and operation capabilities for all available machine types. The objective is to find the minimum-cost set of flow-line cells that is capable of producing the desired part mix. A similarity coefficient based on the longest common operation subsequence between part types is defined and used to group parts into independent, flow-line families. An algorithm is developed for finding a composite operation supersequence for each family. Given machine options for each operation in this sequence, the optimal machine sequence and capacity for each cell is then found by solving a shortest path problem on an augmented graph. The method is shown to be efficient and computational results are reported.     

Development of group setup strategies for makespan minimisation in PCB assembly

Balancing setup effort and actual production time is an important issue in medium-variety, medium-volume printed circuit board (PCB) assembly. By grouping batches of similar PCB types to be processed with a common machine setup, the total time required for setting up the component feeders in the magazine of the placement machine can be reduced. On the other hand, the assembly times per PCB increase, since it is no longer possible to optimise the feeder locations in the magazine for each PCB type individually. In order to balance the savings in setup time and the increase in assembly time and to minimise the global makespan, we propose efficient grouping procedures which include machine-specific algorithms for fine-tuning the machine operations for a group of PCBs. Hence, the actual placement times are reflected much more accurately, compared with conventional grouping procedures which merely analyse the component similarity between pairs of PCBs. Two different agglomerative clustering techniques are proposed. One is based on average linkage clustering, the other on a novel hierarchical clustering approach using an inclusion tree representation of the PCB types. Both take the limited capacity of the component magazine into account. We demonstrate the effectiveness of our approach in an extensive numerical investigation of a single-gantry collect-and-place machine equipped with a rotary placement head and an interchangeable feeder trolley. Compared to conventional methodologies, the proposed group setup strategies reduce the global makespan for a given number of batches significantly.