Route Search Method for Railway Replacement Buses Adopting Ant Colony Optimization

In recent years, Japan, and especially rural areas have faced the growing problems of debt-ridden local railway lines along with the population decline and aging population. Therefore, it is best to consider the discontinuation of local railway lines and introduce replacement buses to secure the transportation methods of the local people especially in rural areas. Based on the above background, targeting local railway lines that may be discontinued in the near future, appropriate bus stops when provided with potential bus stops were selected, the present study proposed a method that introduces routes for railway replacement buses adopting ant colony optimization (ACO). The improved ACO was designed and developed based on the requirements set concerning the route length, number of turns, road width, accessibility of railway lines and zones without bus stops as well as the constraint conditions concerning the route length, number of turns and zones without bus stops. Original road network data were generated and processed adopting a geographic information systems (GIS), and these are used to search for the optimal route for railway replacement buses adopting the improved ACO concerning the 8 zones on the target railway line (JR Kakogawa line). By comparing the improved ACO with Dijkstra’s algorithm, its relevance was verified and areas needing further improvements were revealed.

Study on boundary search method for DFM mesh generation

The boundary mesh of the casting model was determined by direct calculation on the triangular facets extracted from the STL file of the 3D model. Then the inner and outer grids of the model were identified by the algorithm in which we named Inner Seed Grid Method. Finally, a program to automatically generate a 3D FDM mesh was compiled. In the paper, a method named Triangle Contraction Search Method (TCSM) was put forward to ensure not losing the boundary grids; while an algorithm to search inner seed grids to identify inner/outer grids of the casting model was also brought forward. Our algorithm was simple, clear and easy to construct program. Three examples for the casting mesh generation testified the validity of the program.

Dual threshold search method for asperity boundary determination based on geodetic and seismic catalog data

As an important model for explaining the seismic rupture mode,the asperity model plays an important role in studying the stress accumulation of faults and the location of earthquake initiation.Taking Qilian-Haiyuan fault as an example,this paper combines geodetic method and b-value method to propose a multi-source observation data fusion detection method that accurately determines the asperity boundary named dual threshold search method.The method is based on the criterion that the b-value asperity boundary should be most consistent with the slip deficit rate asperity boundary.Then the optimal threshold combination of slip deficit rate and b-value is obtained through threshold search,which can be used to determine the boundary of the asperity.Based on this method,the study finds that there are four potential asperities on the Qilian-Haiyuan fault:two asperities(A1 and A2)are on the Tuolaishan segment and the other two asperities(B and C)are on Lenglongling segment and Jinqianghe segment,respectively.Among them,the lengths of asperities A1 and A2 on Tuolaishan segment are 17.0 km and 64.8 km,respectively.And the lower boundaries are 5.5 km and 15.5 km,respectively;The length of asperity B on Lenglongling segment is 70.7 km,and the lower boundary is 10.2 km.The length of asperity C on Jinqianghe segment is 42.3 km,and the lower boundary is 8.3 km.

A New Genetic Algorithm Based on Niche Technique and Local Search Method

The genetic algorithm has been widely used in many fields as an easy robust global search and optimization method. In this paper, a new generic algorithm based on niche technique and local search method is presented under the consideration of inadequacies of the simple genetic algorithm. In order to prove the adaptability and validity of the improved genetic algorithm, optimization problems of multimodal functions with equal peaks, unequal peaks and complicated peak distribution are discussed. The simulation results show that compared to other niching methods, this improved genetic algorithm has obvious potential on many respects, such as convergence speed, solution accuracy, ability of global optimization, etc.

PID Parameters for Tuning and Optimization of a Turbine EngineBased on the Simplex Search Method

A PID parameters tuning and optimization method for a turbine engine based on the simplex search method was proposed. Taking time delay of combustion and actuator into account, a simulation model of a PID control system for a turbine engine was developed. A performance index based on the integral of absolute error （IAE） was given as an objective function of optimization. In order to avoid the sensitivity that resulted from the initial values of the simplex search method, the traditional Ziegler-Nichols method was used to tune PID parameters to obtain the initial values at first, then the simplex search method was applied to optimize PID parameters for the turbine engine. Simulation results indicate that the simplex search method is a reasonable and effective method for PID controller parameters tuning and optimization.

Global Convergence of Curve Search Methods for Unconstrained Optimization

In this paper we propose a new family of curve search methods for unconstrained optimization problems, which are based on searching a new iterate along a curve through the current iterate at each iteration, while line search methods are based on finding a new iterate on a line starting from the current iterate at each iteration. The global convergence and linear convergence rate of these curve search methods are investigated under some mild conditions. Numerical results show that some curve search methods are stable and effective in solving some large scale minimization problems.

Estimation of mass transfer coefficient in ozone absorption by linear least square fitting and Simplex search methods

For physical ozone absorption without reaction,two parametric estimation methods,i.e.the common linear least square fitting and non-linear Simplex search methods,were applied,respectively,to determine the ozone mass transfer coefficient during absorption and both methods give almost the same mass transfer coefficient.While for chemical absorption with ozone decomposition reaction,the common linear least square fitting method is not applicable for the evaluation of ozone mass transfer coefficient due to the difficulty of model linearization for describing ozone concentration dissolved in water.The nonlinear Simplex method obtains the mass transfer coefficient by minimizing the sum of the differences between the simulated and experimental ozone concentration during the whole absorption process,without the limitation of linear relationship between the dissolved ozone concentration and absorption time during the initial stage of absorption.Comparison of the ozone concentration profiles between the simulation and experimental data demonstrates that Simplex method may determine ozone mass transfer coefficient during absorption in an accurate and high efficiency way with wide applicability.

An Efficient Pattern Search Method

Pattern search algorithms is one of most frequently used methods which were designed to solve the derivative-free optimization problems. Such methods get growing need with the development of science, engineering, economy and so on. Inspired by the idea of Hooke and Jeeves, we introduced an integer m in the algorithm which controls the number of steps of iteration update. We mean along the descent direction to allow the algorithm to?go ahead m steps at most to explore whether we can get better solution further. The experiment proved the strategy’s efficiency.

A Hybrid Unit Commitment Approach Incorporating Modified Priority List with Charged System Search Methods

This paper presents a new hybrid approach that combines Modified Priority List (MPL) with Charged System Search (CSS), termed MPL-CSS, to solve one of the most crucial power system’s operational optimization problems, known as unit commitment (UC) scheduling. The UC scheduling problem is a mixed-integer nonlinear problem, highly-dimensional and extremely constrained. Existing meta-heuristic UC solution methods have the problems of stopping at a local optimum and slow convergence when applied to large-scale, heavily-constrained UC applications. In the first step of the proposed method, initial hourly optimum solutions of UC are obtained by Modified Priority List (MPL);however, the obtained UC solution may still be possible to be further improved. Therefore, in the second step, the CSS is utilized to achieve higher quality solutions. The UC is formulated as mixed integer linear programming to ensure the tractability of the results. The proposed method is successfully applied to a popular test system up to 100 units generators for both 24-hr and 168-hr system. Computational results show that both solution cost and execution time are superior to those of published methods.

Electrical Impedance Tomography Based on Direct Search Method

Solution to impedance distribution in electrical impedance tomography （EIT） is an ill-posed nonlinear inverse problem. It is especially difficult to reconstruct an EIT image in the center area of a measured object. Tikhonov regularization with some prior information is a sound regnlarization method for static electrical impedance tomography under the condition that some true impedance distribution information is known a priori. This paper presents a direct search method （DSM） as pretreatment of image reconstruction through which one not only can construct a regularization matrix which may locate in areas of impedance change, but also can obtain an initial impedance distribution more similar to the true impedance distribution, as well as better current modes which can better distinguish the initial distribution and the true distribution. Simulation results indicate that, by using DSM, resolution in the center area of the measured object can be improved significantly.

A FAST SEARCH METHOD BASED ON THE STATISTICAL PROPERTIES OF SIGNAL

The concepts of ordered code-book and the priority of code-vector are proposedin this paper.The statistical properties of a signal are investigated through its coded sequence.Experimental results are presented which provide some insight into the statistical properties ofvector quantized sequences.Based on the given concepts and experimental results,a fast searchmethod for the vector quantization of correlated information sources,such as Gauss-Markovsources,is proposed and has shown its efficiency in simulation results.

PRP-Type Direct Search Methods for Unconstrained Optimization

Three PRP-type direct search methods for unconstrained optimization are presented. The methods adopt three kinds of recently developed descent conjugate gradient methods and the idea of frame-based direct search method. Global convergence is shown for continuously differentiable functions. Data profile and performance profile are adopted to analyze the numerical experiments and the results show that the proposed methods are effective.

Heru Search Method—Unique in the World that Uses Unprecedented Mathematical Formulas and Replaces the Binary Tree Breaking Various Paradigms Like 0(log<i>n</i>)

This paper deals with the efficiency of the search, with a method of organization and storage of the information that allows better results than the research trees or binary trees. No one ever dared to present better results than 0(log n) complexity, and when they wish to improve, they use balanced trees, but they continue to use principles that do not impact the pre-semantic information treatment. The Heru search method has as main characteristic the total or partial substitution of the use of the binary trees, enabling the elimination of the approximate results and informing the user the desired information instead of occurrences by sampling outside the desired information. The breakdown of the 0(log n) paradigm and the refinement of the searches are achieved with the use of a set of unpublished mathematical formulas and concepts called Infinite Series with Multiple Ratios.

Several New Line Search Methods and Their Convergence

In this paper, we propose several new line search rules for solving unconstrained minimization problems. These new line search rules can extend the accepted scope of step sizes to a wider extent than the corresponding original ones and give an adequate initial step size at each iteration. It is proved that the resulting line search algorithms have global convergence under some mild conditions. It is also proved that the search direction plays an important role in line search methods and that the step size approaches mainly guarantee global convergence in general cases. The convergence rate of these methods is also investigated. Some numerical results show that these new line search algorithms are effective in practical computation.

Intelligent Iterated Local Search Methods for Solving Vehicle Routing Problem with Different Fleets

To solve vehicle routing problem with different fleets, two methodologies are developed. The first methodology adopts twophase strategy. In the first phase, the improved savings method is used to assign customers to appropriate vehicles. In the second phase, the iterated dynasearch algorithm is adopted to route each selected vehicle with the assigned customers. The iterated dynasearch algorithm combines dynasearch algorithm with iterated local search algorithm based on random kicks. The second methodplogy adopts the idea of cyclic transfer which is performed by using dynamic programming algorithm, and the iterated dynasearch algorithm is also embedded in it. The test results show that both methodologies generate better solutions than the traditional method, and the second methodology is superior to the first one.

基于Elasticsearch的挂号系统设计与实现

目的:设计并实现基于Elasticsearch的挂号系统,解决传统挂号系统预约挂号方式单一和搜索挂号平台信息片面等问题,以满足患者日益增长的多元化和智能化就诊需求。方法:采用浏览器与服务器(B/S)架构实现挂号系统设计,前端使用有机对象描述语言(NOODL)渲染界面,并通过Typescript实现函数方法和接口数据交互,Elasticsearch搜索引擎实现高效的搜索功能。后端通过基于边的云对象存储(ECOS)系统处理数据请求,并将业务数据存储在MySQL数据库中。系统包括应用层、服务层和存储层3层架构,可实现登录注册、搜索预约、链接预约、扫码预约、医生设置预约信息等功能。结果:基于Elasticsearch的挂号系统可实现线上搜索预约、医院专属链接预约、扫码预约等多种预约挂号方式,适用于Web和移动设备等多个平台。截止2023年6月,系统拥有医生219人,服务19903例患者,完成预约62737次,为患者就医节省大量时间,提高了医院运转效率。结论:基于Elasticsearch的挂号系统能够满足患者的多元化和智能化就诊需求,为患者提供全面、准确及智能的预约诊疗服务,有效提高诊疗效率。

Subspace Search Method for Quadratic Programming With BoxConstraints

A subspace search method for solving quadratic programming with box constraints is presented in this paper. The original problem is divided into many independent subproblem at an initial point, and a search direction is obtained by solving each of the subproblem, as well as a new iterative point is determined such that the value of objective function is decreasing. The convergence of the algorithm is proved under certain assumptions, and the numerical results are also given.

A New Direct Search Method Based on Separable Fractional Interpolation Model

In this paper, we propose a new separable fractional interpolation model which can be established by 2n interpolation points where n is the number of variables. Based on this model, a new direct search method is presented. In this method, a new iterate is determined by solving the fractional interpolation model in trust region. Under mild assumptions, the convergence results of this method are given and proved, Numerical experiments show that the new method is promising.

SUBSPACE SEARCH METHOD FOR A CLASS OF LEAST SQUARES PROBLEM

Presents information on a study which described a subspace search method for solving a class of least squares problem. Derivation of the algorithm; Convergence results; Modification of algorithm and applications.

THE ACCELERATED SEARCH-EXTENSION METHOD FOR COMPUTING MULTIPLE SOLUTIONS OF SEMILINEAR PDEs

In this paper, we propose an accelerated search-extension method （ASEM） based on the interpolated coefficient finite element method, the search-extension method （SEM） and the two-grid method to obtain the multiple solutions for semilinear elliptic equations. This strategy is not only successfully implemented to obtain multiple solutions for a class of semilinear elliptic boundary value problems, but also reduces the expensive computation greatly. The numerical results in I-D and 2-D cases will show the efficiency of our approach.