scholarly journals Reducing labor intensity when computing optimal technical characteristics of aerial ropeways

2021 ◽  
Vol 49 (1) ◽  
pp. 72-77
Author(s):  
Alexander Lagerev ◽  
Igor Lagerev
Keyword(s):  
Objective Function ◽  
Algebraic Equation ◽  
Computational Efficiency ◽  
Optimization Problem ◽  
Minimum Point ◽  
Nonlinear Algebraic Equation ◽  
Labor Intensity ◽  
Mathematical Methods ◽  
Optimization Task ◽  
Optimal Values

The article develops a procedure for optimizing the technical characteristics of ropeways - the step and the height of intermediate towers, and carrying ropes tension force. The optimization problem was based on the minimization of the tower structures cost. The reduction of computing labor intensity is based on the fact that the position of the minimum point of the objective function will be tied to one of the optimization restrictions. This allowed us to propose two ways to reduce the labor intensity of computing: a) reduction in the dimension of the optimization problem; b) replacement of the search for the minimum of the objective function with the solution of the nonlinear algebraic equation. The article shows that the proposed algorithm has increased computational efficiency. The algorithm allows us to obtain the same optimal values of technical characteristics of ropeways as in the solution of the previously developed optimization task but using simpler mathematical methods.

scholarly journals METHODS OF FORMULATING AND SOLVING OPTIMIZATION PROBLEMS OF CUTTING LOGS OF LARGE SIZE BY BAR-SAWING METHOD WITH CUTTING OUT ONE BAR AND FIVE PAIRS OF SIDE EDGING BOARDS WITH SUBSEQUENT SAWING LUMBER FOR EDGED BOARDS

2017 ◽  
Vol 7 (1) ◽  
pp. 137-150
Author(s):  
Агапов ◽  
Aleksandr Agapov
Keyword(s):  
Mathematical Model ◽  
Objective Function ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Target Function ◽  
Cross Sectional ◽  
Optimization Task ◽  
Cutting Out ◽  
The Mathematical Model ◽  
The Relationship

For the first time the mathematical model of task optimization for this scheme of cutting logs, including the objective function and six equations of connection. The article discusses Pythagorean area of the logs. Therefore, the target function is represented as the sum of the cross-sectional areas of edging boards. Equation of the relationship represents the relationship of the diameter of the logs in the vertex end with the size of the resulting edging boards. This relationship is described through the use of the Pythagorean Theorem. Such a representation of the mathematical model of optimization task is considered a classic one. However, the solution of this mathematical model by the classic method is proved to be problematic. For the solution of the mathematical model we used the method of Lagrange multipliers. Solution algorithm to determine the optimal dimensions of the beams and side edging boards taking into account the width of cut is suggested. Using a numerical method, optimal dimensions of the beams and planks are determined, in which the objective function takes the maximum value. It turned out that with the increase of the width of the cut, thickness of the beam increases and the dimensions of the side edging boards reduce. Dimensions of the extreme side planks to increase the width of cut is reduced to a greater extent than the side boards, which are located closer to the center of the log. The algorithm for solving the optimization problem is recommended to use for calculation and preparation of sawing schedule in the design and operation of sawmill lines for timber production. When using the proposed algorithm for solving the optimization problem the output of lumber can be increased to 3-5 %.

Shape Optimization of Hydraulic Structures: an Example of an Optimum Design of a Fish Passage

10.29007/2k64 ◽  
2018 ◽  
Author(s):  
Pat Prodanovic ◽  
Cedric Goeury ◽  
Fabrice Zaoui ◽  
Riadh Ata ◽  
Jacques Fontaine ◽  
...  
Keyword(s):  
Numerical Model ◽  
Shape Optimization ◽  
Objective Function ◽  
Optimum Design ◽  
Optimization Problem ◽  
A Priori ◽  
Coupled System ◽  
Fish Passage ◽  
Hydraulic Structures ◽  
Design Variables

This paper presents a practical methodology developed for shape optimization studies of hydraulic structures using environmental numerical modelling codes. The methodology starts by defining the optimization problem and identifying relevant problem constraints. Design variables in shape optimization studies are configuration of structures (such as length or spacing of groins, orientation and layout of breakwaters, etc.) whose optimal orientation is not known a priori. The optimization problem is solved numerically by coupling an optimization algorithm to a numerical model. The coupled system is able to define, test and evaluate a multitude of new shapes, which are internally generated and then simulated using a numerical model. The developed methodology is tested using an example of an optimum design of a fish passage, where the design variables are the length and the position of slots. In this paper an objective function is defined where a target is specified and the numerical optimizer is asked to retrieve the target solution. Such a definition of the objective function is used to validate the developed tool chain. This work uses the numerical model TELEMAC- 2Dfrom the TELEMAC-MASCARET suite of numerical solvers for the solution of shallow water equations, coupled with various numerical optimization algorithms available in the literature.

scholarly journals Nonnegative Signal Decomposition with Supervision

2013 ◽  
Vol 2013 ◽  
pp. 1-8
Author(s):  
Teng Li ◽  
Huan Chang ◽  
Jun Wu
Keyword(s):  
Objective Function ◽  
Image Classification ◽  
Pattern Classification ◽  
Optimization Problem ◽  
Real Data ◽  
Classification Performance ◽  
Signal Decomposition ◽  
Weak Supervision ◽  
Training Samples ◽  
Novel Algorithm

This paper presents a novel algorithm to numerically decompose mixed signals in a collaborative way, given supervision of the labels that each signal contains. The decomposition is formulated as an optimization problem incorporating nonnegative constraint. A nonnegative data factorization solution is presented to yield the decomposed results. It is shown that the optimization is efficient and decreases the objective function monotonically. Such a decomposition algorithm can be applied on multilabel training samples for pattern classification. The real-data experimental results show that the proposed algorithm can significantly facilitate the multilabel image classification performance with weak supervision.

scholarly journals Optimal design of a DC MHD pump by simulated annealing method

2014 ◽  
Vol 11 (2) ◽  
pp. 339-350
Author(s):  
Khadidja Bouali ◽  
Fatima Kadid ◽  
Rachid Abdessemed
Keyword(s):  
Simulated Annealing ◽  
Optimal Design ◽  
Objective Function ◽  
Design Problem ◽  
Design Methodology ◽  
Optimization Problem ◽  
Optimization Procedure ◽  
Simulated Annealing Method ◽  
Direct Interpretation ◽  
Annealing Method

In this paper a design methodology of a magnetohydrodynamic pump is proposed. The methodology is based on direct interpretation of the design problem as an optimization problem. The simulated annealing method is used for an optimal design of a DC MHD pump. The optimization procedure uses an objective function which can be the minimum of the mass. The constraints are both of geometrics and electromagnetic in type. The obtained results are reported.

scholarly journals Table cartogram generation as an optimization problem

2019 ◽  
Vol 1 ◽  
pp. 1-2 ◽  
Author(s):  
Mao Li ◽  
Ryo Inoue
Keyword(s):  
Objective Function ◽  
Least Squares ◽  
Optimization Problem ◽  
Data Representation ◽  
Linear Least Squares ◽  
Original Table ◽  
Outer Border ◽  
Limited Degree ◽  
The Difference ◽  
Operation Results

<p><strong>Abstract.</strong> A table cartogram, visualization of table-form data, is a rectangle-shaped table in which each cell is transformed to express the magnitude of positive weight by its area while maintaining the adjacency relationship of cells in the original table. Winter (2011) applies an area cartogram generation method of Gastner and Newman (2004) for their generation, and Evans et al. (2018) proposes a new geometric procedure. The rows and columns on a table cartogram should be easily recognized by readers, however, no methods have focused to enhance the readability. This study proposes a method that defines table cartogram generation as an optimization problem and attempts to minimize vertical and horizontal deformation. Since the original tables are comprised of regular quadrangles, this study uses quadrangles to express cells in a table cartogram and fixes the outer border to attempt to retain the shape of a standard table.</p><p>This study proposes a two-step approach for table cartogram generation with cells that begin as squares and with fixed outer table borders. The first step only adjusts the vertical and horizontal borders of cells to express weights to the greatest possible degree. All cells maintain their rectangular shape after this step, although the limited degree of freedom of this operation results in low data representation accuracy. The second step adapts the cells of the low-accuracy table cartogram to accurately fit area to weight by relaxing the constraints on the directions of borders of cells. This study utilizes an area cartogram generation method proposed by Inoue and Shimizu (2006), which defines area cartogram generation as an optimization problem. The formulation with vertex coordinate parameters consists of an objective function that minimizes the difference between the given data and size of each cell, and a regularization term that controls the changes of bearing angles. It is formulated as non-linear least squares, and is solved through the iteration of linear least squares by linearizing the problem at the coordinates of vertices and updating the estimated coordinates until the value of the objective function becomes small enough.</p>

scholarly journals Optimizing community detection in social networks using antlion and K-median

2019 ◽  
Vol 8 (4) ◽  
Author(s):  
Amany A. Naem ◽  
Neveen I. Ghali
Keyword(s):  
Social Networks ◽  
Objective Function ◽  
Community Detection ◽  
Optimization Problem ◽  
Real Life ◽  
Optimization Methods ◽  
Population Based ◽  
Detection Problem ◽  
Network Communities ◽  
Antlion Optimization

Antlion Optimization (ALO) is one of the latest population based optimization methods that proved its good performance in a variety of applications. The ALO algorithm copies the hunting mechanism of antlions to ants in nature. Community detection in social networks is conclusive to understanding the concepts of the networks. Identifying network communities can be viewed as a problem of clustering a set of nodes into communities. k-median clustering is one of the popular techniques that has been applied in clustering. The problem of clustering network can be formalized as an optimization problem where a qualitatively objective function that captures the intuition of a cluster as a set of nodes with better in ternal connectivity than external connectivity is selected to be optimized. In this paper, a mixture antlion optimization and k-median for solving the community detection problem is proposed and named as K-median Modularity ALO. Experimental results which are applied on real life networks show the ability of the mixture antlion optimization and k-median to detect successfully an optimized community structure based on putting the modularity as an objective function.

scholarly journals THE STATIC OPTIMIZATION TASK OF OPTIMAL DESIGN OF NONLINEAR ELECTRONIC SCHEME

2019 ◽  
pp. 109-115
Author(s):  
Didmanidze Ibraim ◽  
Donadze Mikheil
Keyword(s):  
Optimal Design ◽  
Optimality Criteria ◽  
Pareto Optimal Solutions ◽  
Optimal Solutions ◽  
Design Task ◽  
Optimization Task ◽  
Minimum Capacity ◽  
Optimal Values ◽  
The Given ◽  
Selection Of

The article deals with such an important selection of the elements of electronic scheme of the given configuration, when the certain requirements of technical task are satisfied and at the same time the selected optimality criteria reach the extreme value. The gives task has been solved by the method of one-criterion optimization, in particular, the method of center gravity. To formalize the given scheme we have compiled a mathematical model of optimization, which considers the requirements of technical task. The optimal design task of the presented electronic scheme was brought to the task of multi criteria optimization. The computational experiments have been resulted in the Pareto-optimal solutions, from which there was selected a compromise on that corresponds to the minimum capacity, required by the scheme. According to the optimal values of resistors, we have conducted a computerized analysis of the transient process of the given electronic scheme with the help of a computer program Electronics Workbench.

Network Centric Warfare as Complex Optimization: An Evolutionary Approach

2016 ◽  
Vol 15 (2) ◽  
pp. 93-105
Author(s):  
Zoltán Jobbágy
Keyword(s):  
Optimization Problem ◽  
Fitness Landscape ◽  
Balance Theory ◽  
Military Operations ◽  
Shifting Balance Theory ◽  
Number Of Genes ◽  
Shifting Balance ◽  
Complex Optimization ◽  
Optimal Values ◽  
Different Characteristics

Military operations are very complex undertakings. However, complexity is not a feature unique to military operations. When biologists wanted to understand the properties of gene mutation they also faced complexity. Confronted by a large number of genes featuring different characteristics, a difficult-to-decode interac- tion among those genes, and an environment that could not be excluded as a factor, Sewell Wright introduced the shifting balance theory, also known as the theory of the fitness landscape. The theory allows complexity to be seen as a process that rests on adaptation and mutation. These two processes are also central to military operations as it is imperative to offset the changing conditions coming both from the environment and the interaction with the enemy. In the article the author uses Wright’s theory to help see military operations as a complex optimization problem that includes approximations and estimations regarding optimal values.

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