Location and Capacity Manufacturing Calculation of Electric Vehicle Charging Station Based on Queuing Theory

With the rapid development of industry and manufacturing, the world vigorously promotes green environmental protection, the construction of charging station is particularly important. It is urgent to study the location and capacity of charging station. In this paper, we will analyze the charging behavior of electric vehicles, and combined with the queuing theory model of electric vehicles, optimize the number of chargers by using the minimum objective function of the comprehensive cost of building charging stations. According to the maximum access power allowed by the distribution network, the service radius and scale of the target charging station are finally determined, and then 0-1 planning is used to finally determine the construction site. At the end, we give a specific example analysis to verify the effectiveness of the research results.

Neutrosophic Number Optimization Models and Their Application in the Practical Production Process

In order to simplify the complex calculation and solve the difficult solution problems of neutrosophic number optimization models (NNOMs) in the practical production process, this paper presents two methods to solve NNOMs, where Matlab built-in function “fmincon()” and neutrosophic number operations (NNOs) are used in indeterminate environments. Next, the two methods are applied to linear and nonlinear programming problems with neutrosophic number information to obtain the optimal solution of the maximum/minimum objective function under the constrained conditions of practical productions by neutrosophic number optimization programming (NNOP) examples. Finally, under indeterminate environments, the fit optimal solutions of the examples can also be achieved by using some specified indeterminate scales to fulfill some specified actual requirements. The NNOP methods can obtain the feasible and flexible optimal solutions and indicate the advantage of simple calculations in practical applications.

Implementasi Fuzzy C-Means dan Possibilistik C-Means Pada Data Performance Mahasiswa

Students are the most important component in a university, especially private universities especially Universitas Islam Darul ‘ulum (Unisda) Lamongan. One of the most important roles of students for higher education is achievement. This study aims to determine the role of Fuzzy Clustering in classifying student performance data. The data includes GPA (Grade Point Average), ECCU (Extra-Curricular Credit Unit), attendance, and students' willingness to learn. So that groups of students who have the potential to have achievements can be identified. In this case, the grouping of student performance data uses Fuzzy Clustering by applying the Fuzzy C-Means (FCM) and Possibilistic C-Means (PCM) algorithms with the help of Matlab. In the FCM algorithm, the membership degree is updated so as to produce a minimum objective function value. Meanwhile, the PCM algorithm uses a T matrix, which shows the peculiarities of the data which are also based on minimizing the objective function.

Optimized design of a semimetal gasket operating in flange-bolted joints

The paper presents a new design of semimetal gasket, which has been subjected to the optimization process. The main objective function was to achieve the maximum elastic recovery of the gasket at imposed functional and strength limitations. The objective function was described indirectly in the form of the required minimum angle of the gasket’s unload curve inclination, which was a measure of the average value of the elastic modulus at unloading. Strength limitations resulted from not exceeding the ultimate stress of the materials, while functional limitations imposed the achievement of proper contact pressure that ensures a given level of tightness class. The characteristic dimensions describing the cross-section of the gasket’s core were described by five descriptive parameters. As a result of the interrelationship of these parameters, 210 construction models were created that were subjected to compression simulations. This problem was solved using the Finite Element Method. The variant of the gasket fulfilling the imposed limitations and the required minimum objective function was tested experimentally.

Minimizing the Weight of Cantilever Beam via Metaheuristic Methods by Using Different Population-Iteration Combinations

Since a long time, metaheuristic algorithms are benefited to detect the best results for any optimization problem. Furthermore, these methods are used to prevent of time, effort and cost losses, while they are performing the optimization process. Hence, in this study, a cantilever beam model, which is one of the structural optimization problem from civil engineering area, was handled with the aim of minimization of the total weight by find the optimum section values consisting of hollow section depths and widths. For this reason, three different methods including the algorithms that artificial bee colony (ABC), bat (BA), and a modified bat (MBA) combining of BA with Lévy flight, were operated. Additionally, several applications previously carried out for this model, were presented in order to compare of optimization results (minimum objective function with optimum design variable values), and success of proposed algorithm was showed with statistical results and optimization parameter values.

Finding Best Clustering For Big Networks with Minimum Objective Function by Using Probabilistic Tabu Search

Fuzzy C-means (FCM) is a clustering method used for collecting similar data elements within the group according to specific measurements. Tabu is a heuristic algorithm. In this paper, Probabilistic Tabu Search for FCM implemented to find a global clustering based on the minimum value of the Fuzzy objective function. The experiments designed for different networks, and cluster’s number the results show the best performance based on the comparison that is done between the values of the objective function in the case of using standard FCM and Tabu-FCM, for the average of ten runs.

Optimizing service life of conveyor belts while transporting bulk load

The paper considers problems concerning optimization of service life of a conveyor belt in terms of its bulk material loading. Statement of the problem of belt life optimization is in the determining minimum of difference between squared velocity of a conveyor belt and projection of horizontal component of the load velocity when it contacts a belt onto the belt motion plane. The problem was solved numerically taking into consideration the objective function, varied parameters, and their limitation. Cases of direct-flow loading and loading with the help of special devices with straight and curved trough profiles have been analyzed. Regularities of changes in the belt service life due to significant factors in terms of direct-flow loading and loading with special device have been obtained to perform comparative analysis of different variants in terms of similar value of the objective function. The variants with maximum belt life and minimum objective function have been selected. For short conveyors, in terms of direct-flow loading, belt life decreases by 1.5–2.0 times comparing to the use of a loading device, and in terms of long conveyors, it decreases by 5–6 times, if value of the objective function is 0.5–1.0 m2/s2.

Route Choice in Subway Station during Morning Peak Hours: A Case of Guangzhou Subway

This paper is aimed at crowding phenomenon in the subway. As passengers are inclined to choose the route with minimum disutility, we put forward a route choice model which is constructed to achieve minimum objective function of feasibility for the optimal solution. Meanwhile we set passenger volume threshold values according to capacity of facilities. In the case of actual capacity exceeding the threshold, the decision node of constrained route will be selected; computing procedure about searching decision points will be presented. Then we should set rational restrictions at the decision node of the minimum utility function route to prevent too many passengers’ access to platform. Through certification, this series of methods can effectively ensure the safety of the station efficient operation.

Pipeline Parameter Identification and Leak Localization Using Experimental Data

Pipeline systems are important in many fields of real life to distribute fluids from one location to another. Leakage from such pipeline systems poses serious problems from the technical, environmental and economic points of view. Early leak detection and localization is, therefore, important for real life applications. In this paper, an experimental study is conducted to collect the pressure head measurements at a number of nodes along a pipeline carrying oil for both the healthy and leaky cases. The experimentally measured data are utilized to identify the leak factor and coefficient of friction of the considered pipeline. The identified parameters are utilized by the propose localization scheme to determine the leak location. The identification is implemented by a window marching technique that uses the collected pressure head measurements and seeking the minimum objective function that represents the mismatch between the measured and numerically modeled pipeline variables. Monte Carlo simulation results are reported to demonstrate the effectiveness of the proposed parameter identification and leak localization techniques.

Practical Optimization Algorithm for Discrete Variables

In order to solve the optimization problems of discrete variable in mechanism design, beginning vertexes to meet all of performance restriction conditions can be given by the technician from upper boundary of design variables by means of man-machine interactive method. Objective function of each beginning vertex is calculated and arranged from small to large, the vertex of maximum and minimum of objective function are found. The difference between the vertex of minimum and maximum of objective function are calculated and new point is made up from the minimum point and the difference. The new point is used in stead of the vertex of the maximum objective function if the objective function of the new point is less than the maximum of beginning vertexes. The new composite figure is made up again and the new point is calculated until all design variables reach to under boundary. Then the vertex of minimum objective function is regarded to as the optimization point. This method is very fit for the optimization of discrete variables of low dimension and is higher calculation efficiency because the hominine brightness is combined with the high speed calculation ability.