A deterministic sequential maximin Latin hypercube design method using successive local enumeration for metamodel-based optimization

Space-filling and projective properties of design of computer experiments methods are desired features for metamodelling. To enable the production of high-quality sequential samples, this article presents a novel deterministic sequential maximin Latin hypercube design (LHD) method using successive local enumeration, notated as sequential-successive local enumeration (S-SLE). First, a mesh-mapping algorithm is proposed to map the positions of existing points into the new hyper-chessboard to ensure the projective property. According to the maximin distance criterion, new sequential samples are generated through successive local enumeration iterations to improve the space-filling uniformity. Through a number of comparative studies, several appealing merits of S-SLE are demonstrated: (1) S-SLE outperforms several existing LHD methods in terms of sequential sampling quality; (2) it is flexible and robust enough to produce high-quality multiple-stage sequential samples; and (3) the proposed method can improve the overall performance of sequential metamodel-based optimization algorithms. Thus, S-SLE is a promising sequential LHD method for metamodel-based optimization.     

A two-stage path planning approach for multiple car-like robots based on PH curves and a modified harmony search algorithm

In this article, collision-avoidance path planning for multiple car-like robots with variable motion is formulated as a two-stage objective optimization problem minimizing both the total length of all paths and the task’s completion time. Accordingly, a new approach based on Pythagorean Hodograph (PH) curves and Modified Harmony Search algorithm is proposed to solve the two-stage path-planning problem subject to kinematic constraints such as velocity, acceleration, and minimum turning radius. First, a method of path planning based on PH curves for a single robot is proposed. Second, a mathematical model of the two-stage path-planning problem for multiple car-like robots with variable motion subject to kinematic constraints is constructed that the first-stage minimizes the total length of all paths and the second-stage minimizes the task’s completion time. Finally, a modified harmony search algorithm is applied to solve the two-stage optimization problem. A set of experiments demonstrate the effectiveness of the proposed approach.     

Self-adaptive multi-objective harmony search for optimal design of water distribution networks

In multi-objective optimization computing, it is important to assign suitable parameters to each optimization problem to obtain better solutions. In this study, a self-adaptive multi-objective harmony search (SaMOHS) algorithm is developed to apply the parameter-setting-free technique, which is an example of a self-adaptive methodology. The SaMOHS algorithm attempts to remove some of the inconvenience from parameter setting and selects the most adaptive parameters during the iterative solution search process. To verify the proposed algorithm, an optimal least cost water distribution network design problem is applied to three different target networks. The results are compared with other well-known algorithms such as multi-objective harmony search and the non-dominated sorting genetic algorithm-II. The efficiency of the proposed algorithm is quantified by suitable performance indices. The results indicate that SaMOHS can be efficiently applied to the search for Pareto-optimal solutions in a multi-objective solution space.     

A hybrid optimization method of harmony search and opposition-based learning

The harmony search (HS) method is an emerging meta-heuristic optimization algorithm. However, like most of the evolutionary computation techniques, it sometimes suffers from a rather slow search speed, and fails to find the global optimum in an efficient way. In this article, a hybrid optimization approach is proposed and studied, in which the HS is merged together with the opposition-based learning (OBL). The modified HS, namely HS-OBL, has an improved convergence property. Optimization of 24 typical benchmark functions and an optimal wind generator design case study demonstrate that the HS-OBL can indeed yield a superior optimization performance over the regular HS method.     

A novel hybrid combination optimization algorithm based on search area segmentation and fast Fourier transform

A novel hybrid optimization algorithm combining search area segmentation technique and the fast Fourier transform (HSAS/FFT) is presented to solve the numerical optimization problems. Firstly, the spectrum of each dimension of the objective function can be acquired by the FFT. The search space is segmented by using the spectrum to ensure that each subspace is unimodal. Secondly, the population of subspaces is produced and the optimal individual can be obtained by gradient descent algorithm. Finally, the local optimal solution in the optimal subspace is generated by the binary search algorithm. Make the optimal individual the new search space and repeat the process until meeting the termination condition. The proposed HSAS/FFT was tested on the CEC2017 benchmark, which evaluates the performance of the proposed algorithm on solving global optimization problems. Results obtained show that HSAS/FFT has an excellent performance and better convergence speed in comparison with some of the state-of-the-art algorithms.     

Image segmentation model based on adaptive adjustment of global and local information

In this article, an adaptive mixture model for image segmentation that synthesizes both global information and local information using a new adaptive balance function has been proposed. Given the variety of possible image characteristics that may have to be processed, the proposed model can adaptively adjust the weighting to drive curve evolution trends and states. In this way, the intensity information of weak boundaries and complex backgrounds can be extracted more precisely, thus enabling the model to produce better results for low‐contrast images and complex structures. In addition, a Gaussian filtering process has been added to the model to smooth and standardize the level set function, and a parameter has been introduced to speed up the curve evolution. A penalty term is also used to eliminate the need for complex re‐initialization procedures. Experimental results for various kinds of images efficiently demonstrate the good performance of the proposed model in terms of both speed and accuracy. © 2016 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 26, 179–187, 2016     

A hybrid differential evolution and estimation of distribution algorithm based on neighbourhood search for job shop scheduling problems

Job shop scheduling problem (JSSP) is a typical NP-hard problem. In order to improve the solving efficiency for JSSP, a hybrid differential evolution and estimation of distribution algorithm based on neighbourhood search is proposed in this paper, which combines the merits of Estimation of distribution algorithm and Differential evolution (DE). Meanwhile, to strengthen the searching ability of the proposed algorithm, a chaotic strategy is introduced to update the parameters of DE. Two mutation operators are adopted. A neighbourhood search (NS) algorithm based on blocks on critical path is used to further improve the solution quality. Finally, the parametric sensitivity of the proposed algorithm has been analysed based on the Taguchi method of design of experiment. The proposed algorithm was tested through a set of typical benchmark problems of JSSP. The results demonstrated the effectiveness of the proposed algorithm for solving JSSP.     

全局缺陷和局部缺陷的FPC检测算法研究

为满足柔性电路板缺陷检测在生产线上的检测要求,讨论了基于机器视觉的柔性电路板缺陷实时检测系统试验所需要的关键技术.并且针对传统的基于模板匹配的算法的速度慢、准确率低等问题,提出将柔性电路板的缺陷分为全局缺陷和局部缺陷,对全局缺陷采用直方图匹配和八连通域面积的计算,淘汰两者均存在缺陷的产品;对未被排除的产品图像采用投影匹配和相关系数的计算,实现局部缺陷的识别.改进的算法经过实验验证表明其准确率和检测速度优于传统的检测算法,符合柔性电路板生产线的检测要求.     

Influence of non degenerated joint on the global and local behavior of joined rods

We consider transport (thermoconductivity, diffusion, etc.) problem in a system of joined n-dimensional (n = 2, 3) thin rods, We assume that the joint has the size compared with the characteristic diameter of the rods and the joint is made of materials with transport properties similar to the transport properties of materials of the rods (such joint is referred as non degenerated joint). Using a technique of local perturbation, we construct asymptotic representations of the solution and obtain the limit model for some types of rods and joints. In all the cases, we find that the non degenerated joint is ignored on the global level (e.g., in framework models) and it manifests itself on the local level (in particular, it determines the gradient of the solution in and near the joint).     

Multicriteria evaluation and optimization of the ultrasonic sealing performance based on design of experiments and response surface methodology

Proper closure is an essential packaging quality aspect and can, amongst others, be achieved with ultrasonic sealing. The ultrasonic sealing performance depends on the film type, and the seal settings, such as seal time, applied force and ultrasonic amplitude. Because these parameters are less intuitive than heat seal parameters and optimal settings are undefined for many films, this work presents an efficient approach to evaluate the effect of these settings on the ultrasonic sealing performance. An experimental design defines the experiments to perform. A response surface methodology is then used to model the relation between seal settings and sealing performance. Based on these models, the seal settings are optimized. As there are several criteria to express sealing performance, single‐criteria and multicriteria optimizations are described. The approach was illustrated for a polyethylene terephthalate/linear low‐density polyethylene‐C4 film. The seal settings were optimized to obtain high seal strength, limited ultrasonic horn displacement, and low seal energy. The optimum settings were 0.1 seconds (seal time), 4.32 N/mm (force), and 28.75 μm (amplitude). The predicted optimum strength, horn displacement, and energy were 2.32 N/mm, 40 μm, and 11.66 J, respectively. Besides the optimum, the seal window is also of interest. A broad seal window ensures sufficient seal strength for a wide range of settings. For the polyethylene terephthalate/linear low‐density polyethylene‐C4 film, a strength of ≥90% of the optimum was obtained for 39% of the input combinations within the design space. The presented approach is widely applicable (other films and sealing processes) since it is flexible in the input parameters, design, and responses.