Comparison of nonlinear solvers within continuation method for steady-state variably saturated groundwater flow modelling

2021 ◽  
Vol 36 (4) ◽  
pp. 183-195
Author(s):  
Denis Anuprienko
Keyword(s):  
Steady State ◽  
Line Search ◽  
Search Algorithm ◽  
Continuation Method ◽  
Real Life ◽  
Richards Equation ◽  
Life Problems ◽  
Nonlinear Solvers ◽  
Groundwater Flow Modelling ◽  
Search Approach

Abstract Nonlinearity continuation method, applied to boundary value problems for steady-state Richards equation, gradually approaches the solution through a series of intermediate problems. Originally, the Newton method with simple line search algorithm was used to solve the intermediate problems. In the present paper, other solvers such as Picard and mixed Picard–Newton methods are considered, combined with slightly modified line search approach. Numerical experiments are performed with advanced finite volume discretizations for model and real-life problems.

scholarly journals Robustness and Stability in Constraint Programming under Dynamism and Uncertainty

2014 ◽  
Vol 49 ◽  
pp. 49-78 ◽  
Author(s):  
L. Climent ◽  
R. J. Wallace ◽  
M. A. Salido ◽  
F. Barber
Keyword(s):  
Constraint Programming ◽  
Original Problem ◽  
Search Algorithm ◽  
Real Life ◽  
Dynamic Environment ◽  
Dynamic Environments ◽  
General Purpose ◽  
Constraint Satisfaction Problems ◽  
Life Problems ◽  
Random Instances

Many real life problems that can be solved by constraint programming, come from uncertain and dynamic environments. Because of the dynamism, the original problem may change over time, and thus the solution found for the original problem may become invalid. For this reason, dealing with such problems has become an important issue in the fields of constraint programming. In some cases, there exist extant knowledge about the uncertain and dynamic environment. In other cases, this information is fragmentary or unknown. In this paper, we extend the concept of robustness and stability for Constraint Satisfaction Problems (CSPs) with ordered domains, where only limited assumptions need to be made as to possible changes. We present a search algorithm that searches for both robust and stable solutions for CSPs of this nature. It is well-known that meeting both criteria simultaneously is a desirable objective for constraint solving in uncertain and dynamic environments. We also present compelling evidence that our search algorithm outperforms other general-purpose algorithms for dynamic CSPs using random instances and benchmarks derived from real life problems.

A novel hybrid water wave optimization algorithm for solving complex constrained engineering problems

2021 ◽  
Vol 63 (6) ◽  
pp. 560-564
Author(s):  
Dildar Gürses ◽  
Nantiwat Pholdee ◽  
Sujin Bureerat ◽  
Sadiq M. Sait ◽  
Ali Rıza Yıldız
Keyword(s):  
Optimization Algorithm ◽  
Real World ◽  
Water Wave ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Real Life ◽  
Processing Parameters ◽  
Parameters Optimization ◽  
Optimization Approach ◽  
Life Problems

Abstract In this work, a new hybrid optimization algorithm (HWW-NM), which combines the Nelder-Mead local search algorithm with the water wave algorithm, is introduced to solve real-world engineering optimization problems. This paper is one of the first studies in which both the water wave algorithm and the HWW-NM are applied to processing parameters optimization for manufacturing processes. HWW-NM performance is measured using the cantilever beam problem. Additionally, a problem for milling manufacturing optimization is posed and solved to evaluate HWW-NM performance in real-world applications. The results reveal that HWW-NM is an attractive optimization approach for optimizing real-life problems.

Evaluation of EHO Algorithm’s in solving various real-life problems

2020 ◽  
Vol 1 (2) ◽  
pp. 46-60
Author(s):  
Ahmed R. Ridwan
Keyword(s):  
Pid Controller ◽  
Search Algorithm ◽  
Real Life ◽  
Service Selection ◽  
Benchmark Problems ◽  
Herding Behavior ◽  
Life Problems ◽  
Metaheuristic Search ◽  
Pid Controller Tuning ◽  
Hard Problems

Abstract:  This paper, presents a new swarm-based metaheuristic search algorithm, known as Elephant Herding Optimization (EHO), which is proposed for solving various daily real-life problems such as benchmark problems, Service Selection in QoS-Aware Web Service Composition, Energy-Based Localization, PID controller tuning, Appliance Scheduling in Smart Grid identification and other problems. The EHO method is inspired by the herding behavior of elephant group. In nature, elephants live in clans under the leadership of a matriarch (female elephant), while the male elephants separate from their family when they grow up. These two behaviors are used by EHO as two operators: clan updating operator and separating operator, which will be used in the optimizing process. Elephant Herding Optimization (EHO) is used to solve NP-Hard problems.

The Psychologist in the Medical School: An Example of Solving Real-Life Problems

1970 ◽  
Author(s):  
Matisyohu Weisenberg ◽  
Carl Eisdorfer ◽  
C. Richard Fletcher ◽  
Murray Wexler
Keyword(s):  
Medical School ◽  
Real Life ◽  
Life Problems

A Non-Monotone Line Search Combination Technique for Unconstrained Optimization

2014 ◽  
Vol 8 (1) ◽  
pp. 218-221 ◽  
Author(s):  
Ping Hu ◽  
Zong-yao Wang
Keyword(s):  
Global Convergence ◽  
Unconstrained Optimization ◽  
Numerical Experiments ◽  
Line Search ◽  
Optimization Problems ◽  
Search Algorithm ◽  
New Combination ◽  
Combination Rule ◽  
Combination Technique ◽  
Unconstrained Optimization Problems

We propose a non-monotone line search combination rule for unconstrained optimization problems, the corresponding non-monotone search algorithm is established and its global convergence can be proved. Finally, we use some numerical experiments to illustrate the new combination of non-monotone search algorithm’s effectiveness.

scholarly journals AnANN Model Trained on Regional Data in the Prediction of Particular Weather Conditions

2021 ◽  
Vol 11 (11) ◽  
pp. 4757
Author(s):  
Aleksandra Bączkiewicz ◽  
Jarosław Wątróbski ◽  
Wojciech Sałabun ◽  
Joanna Kołodziejczyk
Keyword(s):  
Atmospheric Pressure ◽  
Real Life ◽  
Real Data ◽  
Weather Conditions ◽  
Maximum Temperature ◽  
Air Masses ◽  
Weather Forecasts ◽  
Life Problems ◽  
The World ◽  
The City

Artificial Neural Networks (ANNs) have proven to be a powerful tool for solving a wide variety of real-life problems. The possibility of using them for forecasting phenomena occurring in nature, especially weather indicators, has been widely discussed. However, the various areas of the world differ in terms of their difficulty and ability in preparing accurate weather forecasts. Poland lies in a zone with a moderate transition climate, which is characterized by seasonality and the inflow of many types of air masses from different directions, which, combined with the compound terrain, causes climate variability and makes it difficult to accurately predict the weather. For this reason, it is necessary to adapt the model to the prediction of weather conditions and verify its effectiveness on real data. The principal aim of this study is to present the use of a regressive model based on a unidirectional multilayer neural network, also called a Multilayer Perceptron (MLP), to predict selected weather indicators for the city of Szczecin in Poland. The forecast of the model we implemented was effective in determining the daily parameters at 96% compliance with the actual measurements for the prediction of the minimum and maximum temperature for the next day and 83.27% for the prediction of atmospheric pressure.

scholarly journals Formulating Modes of Cooperative Leaning for Education for Sustainable Development

2021 ◽  
Vol 13 (6) ◽  
pp. 3465
Author(s):  
Jordi Colomer ◽  
Dolors Cañabate ◽  
Brigita Stanikūnienė ◽  
Remigijus Bubnys
Keyword(s):  
Sustainable Development ◽  
Real Life ◽  
Education For Sustainable Development ◽  
Professional Life ◽  
Global Challenges ◽  
Life Problems ◽  
The Face ◽  
Contemporary Education ◽  
The Impact

In the face of today’s global challenges, the practice and theory of contemporary education inevitably focuses on developing the competences that help individuals to find meaningfulness in their societal and professional life, to understand the impact of local actions on global processes and to enable them to solve real-life problems [...]

scholarly journals A Modified Niching Crow Search Approach to Well Placement Optimization

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 857
Author(s):  
Jahedul Islam ◽  
Md Shokor A. Rahaman ◽  
Pandian M. Vasant ◽  
Berihun Mamo Negash ◽  
Ahshanul Hoqe ◽  
...  
Keyword(s):  
Optimization Problem ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Multimodal Optimization ◽  
Test Functions ◽  
Well Placement ◽  
Suggested Approach ◽  
Placement Optimization ◽  
Well Placement Optimization ◽  
Search Approach

Well placement optimization is considered a non-convex and highly multimodal optimization problem. In this article, a modified crow search algorithm is proposed to tackle the well placement optimization problem. This article proposes modifications based on local search and niching techniques in the crow search algorithm (CSA). At first, the suggested approach is verified by experimenting with the benchmark functions. For test functions, the results of the proposed approach demonstrated a higher convergence rate and a better solution. Again, the performance of the proposed technique is evaluated with well placement optimization problem and compared with particle swarm optimization (PSO), the Gravitational Search Algorithm (GSA), and the Crow search algorithm (CSA). The outcomes of the study revealed that the niching crow search algorithm is the most efficient and effective compared to the other techniques.

scholarly journals Derivative-Free King’s Scheme for Multiple Zeros of Nonlinear Functions

Mathematics ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1242
Author(s):  
Ramandeep Behl ◽  
Sonia Bhalla ◽  
Eulalia Martínez ◽  
Majed Aali Alsulami
Keyword(s):  
Iterative Methods ◽  
Fourth Order ◽  
Order Of Convergence ◽  
Real Life ◽  
Multiple Roots ◽  
Computational Results ◽  
Nonlinear Functions ◽  
First Order ◽  
Life Problems ◽  
Derivative Free

There is no doubt that the fourth-order King’s family is one of the important ones among its counterparts. However, it has two major problems: the first one is the calculation of the first-order derivative; secondly, it has a linear order of convergence in the case of multiple roots. In order to improve these complications, we suggested a new King’s family of iterative methods. The main features of our scheme are the optimal convergence order, being free from derivatives, and working for multiple roots (m≥2). In addition, we proposed a main theorem that illustrated the fourth order of convergence. It also satisfied the optimal Kung–Traub conjecture of iterative methods without memory. We compared our scheme with the latest iterative methods of the same order of convergence on several real-life problems. In accordance with the computational results, we concluded that our method showed superior behavior compared to the existing methods.

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