Linear and Nonlinear Problems of Wave Resistance to the Movement of Objects Along Elastic Guides

The textbook discusses methods of optimal design of structures, including methods for minimizing the functions of one and several variables; methods for solving linear and nonlinear programming problems; examples of optimal design of flat steel frames with elements made of rolled and composite I-beams. It is intended for students studying in the specialty 08.05.01 "Construction of unique buildings and structures", undergraduates studying in the training program 08.04.01.24 "Modern technologies of design and construction of buildings and structures", studying the discipline "Nonlinear problems of structural mechanics", as well as for postgraduates of the direction 08.06.01 " Engineering and construction technologies. Construction of buildings and structures", studying the discipline "Construction Mechanics".

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Variational finite-difference methods in linear and nonlinear problems of the deformation of metallic and composite shells (review)

International Applied Mechanics ◽

10.1007/s10778-012-0544-8 ◽

2012 ◽

Vol 48 (6) ◽

pp. 613-687 ◽

Cited By ~ 22

Author(s):

V. A. Maksimyuk ◽

E. A. Storozhuk ◽

I. S. Chernyshenko

Keyword(s):

Finite Difference ◽

Finite Difference Methods ◽

Nonlinear Problems ◽

Composite Shells ◽

Linear And Nonlinear ◽

Difference Methods

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Solutions of linear and nonlinear problems related to torsional rigidity of a beam

Computational Materials Science ◽

10.1016/j.commatsci.2008.11.010 ◽

2009 ◽

Vol 45 (2) ◽

pp. 494-498 ◽

Cited By ~ 8

Author(s):

Alemdar Hasanov ◽

Salih Tatar

Keyword(s):

Torsional Rigidity ◽

Nonlinear Problems ◽

Linear And Nonlinear

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Nonlinear Inertia Weighted Teaching-Learning-Based Optimization for Solving Global Optimization Problem

Computational Intelligence and Neuroscience ◽

10.1155/2015/292576 ◽

2015 ◽

Vol 2015 ◽

pp. 1-15 ◽

Cited By ~ 12

Author(s):

Zong-Sheng Wu ◽

Wei-Ping Fu ◽

Ru Xue

Keyword(s):

Global Optimization ◽

Optimization Problem ◽

Random Number ◽

Nonlinear Problems ◽

Tlbo Algorithm ◽

Teaching Learning Based Optimization ◽

Linear And Nonlinear ◽

Weighted Factor ◽

Teaching Learning ◽

Dynamic Inertia

Teaching-learning-based optimization (TLBO) algorithm is proposed in recent years that simulates the teaching-learning phenomenon of a classroom to effectively solve global optimization of multidimensional, linear, and nonlinear problems over continuous spaces. In this paper, an improved teaching-learning-based optimization algorithm is presented, which is called nonlinear inertia weighted teaching-learning-based optimization (NIWTLBO) algorithm. This algorithm introduces a nonlinear inertia weighted factor into the basic TLBO to control the memory rate of learners and uses a dynamic inertia weighted factor to replace the original random number in teacher phase and learner phase. The proposed algorithm is tested on a number of benchmark functions, and its performance comparisons are provided against the basic TLBO and some other well-known optimization algorithms. The experiment results show that the proposed algorithm has a faster convergence rate and better performance than the basic TLBO and some other algorithms as well.

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