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Number of results: 8
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Abstract

The material presents a real problem inherent in the management of computer systems, namely that of finding the appropriate system settings and thus being able to achieve the expected perfor- mance. The material also presents a prototype which aims to adapt the system in such a way as to achieve the objective, defined as the application efficiency. The prototype uses a resource-oriented mechanism that is built into the OS Workload Manager and is focused on a proposed goal-oriented subsystem based on fuzzy logic, managing resources to make the best use of them, and pursuing translation to the use of system resources, including nondeterministic technology-related factors such as duration of allocation and release of the resources, sharing the resources with the uncapped mode, and the errors of performance measurement.
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Authors and Affiliations

Maciej Młyński
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Abstract

Training a neural network can be a challenging task, particularly when working with complex models and large amounts of training data, as it consumes significant time and resources. This research proposes a hybrid model that combines population-based heuristic algorithms with traditional gradient-based techniques to enhance the training process. The proposed approach involves using a dynamic population-based heuristic algorithm to identify good initial values for the neural network weight vector. This is done as an alternative to the traditional technique of starting with random weights. After several cycles of distributing search agents across the search domain, the training process continues using a gradient-based technique that starts with the best initial weight vector identified by the heuristic algorithm. Experimental analysis confirms that exploring the search domain during the training process decreases the number of cycles needed for gradient descent to train a neural network. Furthermore, a dynamic population strategy is applied during the heuristic search, with objects added and removed dynamically based on their progress. This approach yields better results compared to traditional heuristic algorithms that use the same population members throughout the search process.
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Authors and Affiliations

Amer Mirkhan
1
Numan Çelebi
2
ORCID: ORCID

  1. Sakarya University, Computer Engineering Department
  2. Sakarya University, Information Systems Engineering Department
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Abstract

The paper presents a new elastic scheduling task model which has been used in the uniprocessor node of a control measuring system. This model allows the selection of a new set of periods for the occurrence of tasks executed in the node of a system in the case when it is necessary to perform additional aperiodic tasks or there is a need to change the time parameters of existing tasks. Selection of periods is performed by heuristic algorithms. This paper presents the results of the experimental use of an elastic scheduling model with a GRASP heuristic algorithm.

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Authors and Affiliations

Wiesław Miczulski
Piotr Powroźnik
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Abstract

In this paper,we proposed a modified meta-heuristic algorithm based on the blind naked mole-rat (BNMR) algorithm to solve the multiple standard benchmark problems. We then apply the proposed algorithm to solve an engineering inverse problem in the electromagnetic field to validate the results. The main objective is to modify the BNMR algorithm by employing two different types of distribution processes to improve the search strategy. Furthermore, we proposed an improvement scheme for the objective function and we have changed some parameters in the implementation of the BNMR algorithm. The performance of the BNMR algorithm was improved by introducing several new parameters to find the better target resources in the implementation of a modified BNMR algorithm. The results demonstrate that the changed candidate solutions fall into the neighborhood of the real solution. The results show the superiority of the propose method over other methods in solving various mathematical and electromagnetic problems.
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Bibliography

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Authors and Affiliations

Mohammad Taherdangkoo
1
ORCID: ORCID

  1. Institute of Research and Development, Duy Tan University, Da Nang 550000, Vietnam
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Abstract

Economic Load Dispatch (ELD) is utilized in finding the optimal combination of the real power generation that minimizes total generation cost, yet satisfying all equality and inequality constraints. It plays a significant role in planning and operating power systems with several generating stations. For simplicity, the cost function of each generating unit has been approximated by a single quadratic function. ELD is a subproblem of unit commitment and a nonlinear optimization problem. Many soft computing optimization methods have been developed in the recent past to solve ELD problems. In this paper, the most recently developed population-based optimization called the Salp Swarm Algorithm (SSA) has been utilized to solve the ELD problem. The results for the ELD problem have been verified by applying it to a standard 6-generator system with and without due consideration of transmission losses. The finally obtained results using the SSA are compared to that with the Particle Swarm Optimization (PSO) algorithm. It has been observed that the obtained results using the SSA are quite encouraging.
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Authors and Affiliations

Ramesh Devarapalli
1
ORCID: ORCID
Nikhil Kumar Sinha
1
ORCID: ORCID
Bathina Venkateswara Rao
2
ORCID: ORCID
Łukasz Knypinski
3
ORCID: ORCID
Naraharisetti Jaya Naga Lakshmi
4
ORCID: ORCID
Fausto Pedro García Márquez
5
ORCID: ORCID

  1. Department of EE, B. I. T. Sindri, Dhanbad, Jharkhand – 828123, India
  2. Department of EEE, V R Siddhartha Engineering College (Autonomous), Vijayawada-520007, A.P., India
  3. Poznan University of Technology, Poland
  4. SR Engineering College: Warangal, Telangana, India
  5. Ingenium Research Group, University of Castilla-La Mancha, Spain
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Abstract

The paper presents a novel hybrid cuckoo search (CS) algorithm for the optimization of the line-start permanent magnet synchronous motor (LSPMSM). The hybrid optimization algorithm developed is a merger of the heuristic algorithm with the deterministic Hooke–Jeeves method. The hybrid optimization procedure developed was tested on analytical benchmark functions and the results were compared with the classical cuckoo search algorithm, genetic algorithm, particle swarm algorithm and bat algorithm. The optimization script containing a hybrid algorithm was developed in Delphi Tiburón. The results presented show that the modified method is characterized by better accuracy. The optimization procedure developed is related to a mathematical model of the LSPMSM. The multi-objective compromise function was applied as an optimality criterion. Selected results were presented and discussed.
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Authors and Affiliations

Łukasz Knypiński
1
ORCID: ORCID

  1. Poznan University of Technology, Institute of Electrical Engineering and Electronics, Piotrowo 3a, 60-965 Poznan, Poland
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Abstract

Improving production processes includes not only activities concerning manufacturing itself, but also all the activities that are necessary to achieve the main objectives. One such activity is transport, which, although a source of waste in terms of adding value to the product, is essential to the realization of the production process. Over the years, many methods have been developed to help manage supply and transport in such a way as to reduce it to the necessary minimum. In the paper, the problem of delivering components to a production area using trains and appropriately laid-out carriages was described. It is a milk run stop locations problem (MRSLP), whose proposed solution is based on the use of heuristic algorithms. Intelligent solutions are getting more and more popular in the industry because of the possible advantages they offer, especially those that include the possibility of finding an optimum local solution in a relatively short time and the prevention of human errors. In this paper, the applicability of three algorithms – tabu search, genetic algorithm, and simulated annealing – was explored.
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Authors and Affiliations

Joanna Kochańska
1
Anna Burduk
1
ORCID: ORCID
Dagmara Łapczyńska
1
Kamil Musiał
1

  1. Faculty of Mechanical Engineering, Wroclaw University of Science and Technology, 50-370 Wroclaw, Poland

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