Double integral-balance method to the fractional subdiffusion equation: Approximate solutions, optimization problems to be resolved and numerical simulations

2015 ◽  
Vol 23 (17) ◽  
pp. 2795-2818 ◽  
Author(s):  
Jordan Hristov
Keyword(s):  
Optimization Problems ◽  
Approximate Solutions ◽  
Zero Initial Condition ◽  
Parabolic Profile ◽  
Numerical Studies ◽  
Approximate Integral ◽  
Balance Solution ◽  
Mainardi Function ◽  
Subdiffusion Equation

An approximate integral-balance solution of the fractional subdiffusion equation by a double-integration technique has been conceived. The time-fractional linear subdiffusion equation with Dirichlet boundary condition (and zero initial condition) has been chosen as a test example. Approximations of time-fractional Riemann-Liouville and Caputo derivatives when the distribution is assumed as a parabolic profile with unspecified exponent have been developed. Problems pertinent to determination of the optimal exponent of the parabolic profile and approximations of the time-fractional derivative of by different approaches have been formulated. Solved and unresolved problems in determination of the optimal exponents have been demonstrated. Examples with predetermined quadratic and cubic assumed profiles are analyzed, too. Comparative numerical studies with exact solutions expressed by the Mainardi function in terms of a similarity variable have been performed.

scholarly journals An approximate solution to the transient space-fractional diffusion equation: Integral-balance approach, optimization problems and analyzes

2017 ◽  
Vol 21 (1 Part A) ◽  
pp. 309-321 ◽  
Author(s):  
Jordan Hristov
Keyword(s):  
Diffusion Equation ◽  
Optimization Problems ◽  
Initial Boundary ◽  
Initial Boundary Value Problem ◽  
Approximate Solutions ◽  
Differential Diffusion ◽  
Parabolic Profile ◽  
Approximate Analytical Solutions ◽  
Liouville Fractional Derivative ◽  
Initial Boundary Value

This paper presents approximate analytical solutions of an initial-boundary value problem of fractional partial differential diffusion equation with spatial Riemann-Liouville fractional derivative. The proposed approximate solutions are based on the concept of a finite penetration depth with the integral-balance method and series expansions of the assumed parabolic profile with undefined exponent. Optimization problems referring to optimal exponents of the assumed parabolic have been developed.

scholarly journals Comparative Study of Optimization Algorithms for The Optimal Reservoir Operation

2018 ◽  
Vol 246 ◽  
pp. 01003
Author(s):  
Xinyuan Liu ◽  
Yonghui Zhu ◽  
Lingyun Li ◽  
Lu Chen
Keyword(s):  
Reservoir Operation ◽  
Optimization Problems ◽  
Optimization Algorithms ◽  
Complex Problem ◽  
Optimization Techniques ◽  
Decision Variables ◽  
Handling Methods ◽  
Optimality Algorithm ◽  
Parameter Values

Apart from traditional optimization techniques, e.g. progressive optimality algorithm (POA), modern intelligence algorithms, like genetic algorithms, differential evolution have been widely used to solve optimization problems. This paper deals with comparative analysis of POA, GA and DE and their applications in a reservoir operation problem. The results show that both GA and DES are feasible to reservoir operation optimization, but they display different features. GA and DE have many parameters and are difficult in determination of these parameter values. For simple problems with mall number of decision variables, GA and DE are better than POA when adopting appropriate parameter values and constraint handling methods. But for complex problem with large number of variables, POA combined with simplex method are much superior to GA and DE in time-assuming and quality of optimal solutions. This study helps to select proper optimization algorithms and parameter values in reservoir operation.

scholarly journals EXPERIMENTAL AND NUMERICAL STUDIES OF PRESSURE AND GAP LENGTH EFFECTS ON ENERGY DEPOSITION IN SPARK DISCHARGE

2021 ◽  
pp. 92-97
Author(s):  
K.V. Korytchenko ◽  
I.S. Varshamova ◽  
D.V. Meshkov ◽  
D.P. Dubinin ◽  
R.I. Kovalenko ◽  
...  
Keyword(s):  
Energy Input ◽  
Energy Deposition ◽  
Initial Pressure ◽  
Numerical Studies ◽  
Voltage Probe ◽  
Spark Channel ◽  
Discharge Gap ◽  
Total Discharge ◽  
Channel Development

A study of the influence of the discharge gap length and the initial gas pressure on the energy deposition into the discharge channel was done. The study was conducted at the same total discharge energy. It is experimentally shown that the connection of the voltage probe to the discharge circuit significantly affects the discharge current. The determination of the energy deposited into the spark channel is based on the results of numerical simulation of the spark channel development. Experimentally measured discharge currents at different pressures and the gap length were used as initial data for the calculation. Based on the obtained results, it is determined which of the factors (the initial pressure or the gap length) has the strongest influence on the energy input into the spark channel.

scholarly journals A Dai-Liao Hybrid Hestenes-Stiefel and Fletcher-Revees Methods for Unconstrained Optimization

2021 ◽  
Vol 2 (1) ◽  
pp. 33
Author(s):  
Nasiru Salihu ◽  
Mathew Remilekun Odekunle ◽  
Also Mohammed Saleh ◽  
Suraj Salihu
Keyword(s):  
Unconstrained Optimization ◽  
Line Search ◽  
Optimization Problems ◽  
Convex Combination ◽  
Gradient Methods ◽  
Approximate Solutions ◽  
Step Size ◽  
Conjugacy Condition ◽  
Inexact Line Search ◽  
Wolfe Line Search

Some problems have no analytical solution or too difficult to solve by scientists, engineers, and mathematicians, so the development of numerical methods to obtain approximate solutions became necessary. Gradient methods are more efficient when the function to be minimized continuously in its first derivative. Therefore, this article presents a new hybrid Conjugate Gradient (CG) method to solve unconstrained optimization problems. The method requires the first-order derivatives but overcomes the steepest descent method’s shortcoming of slow convergence and needs not to save or compute the second-order derivatives needed by the Newton method. The CG update parameter is suggested from the Dai-Liao conjugacy condition as a convex combination of Hestenes-Stiefel and Fletcher-Revees algorithms by employing an optimal modulating choice parameterto avoid matrix storage. Numerical computation adopts an inexact line search to obtain the step-size that generates a decent property, showing that the algorithm is robust and efficient. The scheme converges globally under Wolfe line search, and it’s like is suitable in compressive sensing problems and M-tensor systems.

On quasi approximate solutions for nonsmooth robust semi-infinite optimization problems

2019 ◽  
Vol 35 (3) ◽  
pp. 417-426 ◽  
Author(s):  
CHANOKSUDA KHANTREE ◽  
RABIAN WANGKEEREE ◽  
◽  
Keyword(s):  
Constraint Qualification ◽  
Generalized Convexity ◽  
Optimization Problems ◽  
Approximate Solutions ◽  
Data Uncertainty ◽  
Necessary Condition ◽  
Duality Theorems ◽  
Approximate Form ◽  
Locally Lipschitz ◽  
Approximate Duality

This paper devotes to the quasi ε-solution for robust semi-infinite optimization problems (RSIP) involving a locally Lipschitz objective function and infinitely many locally Lipschitz constraint functions with data uncertainty. Under the fulfillment of robust type Guignard constraint qualification and robust type Kuhn-Tucker constraint qualification, a necessary condition for a quasi ε-solution to problem (RSIP). After introducing the generalized convexity, we give a sufficient optimality for such a quasi ε-solution to problem (RSIP). Finally, we also establish approximate duality theorems in term of Wolfe type which is formulated in approximate form.

Development of an Optimization Framework for Parameter Identification and Shape Optimization Problems in Engineering

2011 ◽  
Vol 1 (1) ◽  
pp. 57-79 ◽  
Author(s):  
A. Andrade-Campos
Keyword(s):  
Inverse Problems ◽  
Shape Optimization ◽  
Parameter Identification ◽  
Optimization Problems ◽  
Optimization Methods ◽  
Optimum Shape ◽  
Optimization Framework ◽  
Search Optimization ◽  
Initial Geometry

The use of optimization methods in engineering is increasing. Process and product optimization, inverse problems, shape optimization, and topology optimization are frequent problems both in industry and science communities. In this paper, an optimization framework for engineering inverse problems such as the parameter identification and the shape optimization problems is presented. It inherits the large experience gain in such problems by the SiDoLo code and adds the latest developments in direct search optimization algorithms. User subroutines in Sdl allow the program to be customized for particular applications. Several applications in parameter identification and shape optimization topics using Sdl Lab are presented. The use of commercial and non-commercial (in-house) Finite Element Method codes to evaluate the objective function can be achieved using the interfaces pre-developed in Sdl Lab. The shape optimization problem of the determination of the initial geometry of a blank on a deep drawing square cup problem is analysed and discussed. The main goal of this problem is to determine the optimum shape of the initial blank in order to save latter trimming operations and costs.

scholarly journals A non-exponential extension of Sanov’s theorem via convex duality

2020 ◽  
Vol 52 (1) ◽  
pp. 61-101
Author(s):  
Daniel Lacker
Keyword(s):  
Optimal Transport ◽  
Large Deviation ◽  
Optimization Problems ◽  
Risk Measures ◽  
Approximate Solutions ◽  
Variational Problems ◽  
Dual Pair ◽  
Wasserstein Distance ◽  
Empirical Measures ◽  
Empirical Distributions

AbstractThis work is devoted to a vast extension of Sanov’s theorem, in Laplace principle form, based on alternatives to the classical convex dual pair of relative entropy and cumulant generating functional. The abstract results give rise to a number of probabilistic limit theorems and asymptotics. For instance, widely applicable non-exponential large deviation upper bounds are derived for empirical distributions and averages of independent and identically distributed samples under minimal integrability assumptions, notably accommodating heavy-tailed distributions. Other interesting manifestations of the abstract results include new results on the rate of convergence of empirical measures in Wasserstein distance, uniform large deviation bounds, and variational problems involving optimal transport costs, as well as an application to error estimates for approximate solutions of stochastic optimization problems. The proofs build on the Dupuis–Ellis weak convergence approach to large deviations as well as the duality theory for convex risk measures.

The Combined Closed Form-Perturbation Approach to the Analysis of Mistuned Bladed Disks

1993 ◽  
Vol 115 (4) ◽  
pp. 771-780 ◽  
Author(s):  
M. P. Mignolet ◽  
C.-C. Lin
Keyword(s):  
Probability Density Function ◽  
Probability Density ◽  
Density Function ◽  
Approximate Solutions ◽  
Forced Response ◽  
Perturbation Approach ◽  
Perturbation Techniques ◽  
Step Method ◽  
Bladed Disk

A two-step method is presented for the determination of reliable approximations of the probability density function of the forced response of a randomly mistuned bladed disk. Under the assumption of linearity, an integral representation of the probability density function of the blade amplitude is first derived. Then, deterministic perturbation techniques are employed to produce simple approximations of this function. The adequacy of the method is demonstrated by comparing several approximate solutions with simulation results.

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