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Abstract

‘Hard’ and ‘soft’ methods in analyses of territorial structures’. This article refers to two distinct approaches to investigations of territorial structures and their changes: the ‘intuitive’ of ‘soft’ approach and a more rigid, formalized or ‘hard’ one. The examples of analyzing the regional patterns in Poland over a almost 40 year span are called to illustrate these relations between two methodological standpoints. The conclusion states that both of them are valid and useful, however their strengths can be fully exposed when both are applied in an comprehensive way, supporting each other in a difficult process of investigation multidimensional and dynamic changes of the social territorial systems.
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Authors and Affiliations

Grzegorz Gorzelak
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Abstract

Underground spaces having features such as stability, resistance, and being undetected can play a key role in reducing vulnerability by relocating infrastructures and manpower. In recent years, the competitive business environment and limited resources have mostly focused on the importance of project management in order to achieve its objectives. In this research, in order to find the best balance among cost, time, and quality related to construction projects using reinforced concrete in underground structures, a multi-objective mathematical model is proposed. Several executive approaches have been considered for project activities and these approaches are analyzed via several factors. It is assumed that cost, time, and quality of activities in every defined approach can vary between compact and normal values, and the goal is to find the best execution for activities, achieving minimum cost and the maximum quality for the project. To solve the proposed multi-objective model, the genetic algorithm NSGA-II is used.

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Authors and Affiliations

S.A. Hosseini
A. Akbarpour
H. Ahmadi
B. Aminnejad
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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 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

The paper presents a heuristic approach to the problem of analog circuit diagnosis. Different optimization techniques in the field of test point selection are discussed. Two new algorithms: SALTO and COSMO have been introduced. Both searching procedures have been implemented in a form of the expert system in PROLOG language. The proposed methodologies have been exemplified on benchmark circuits. The obtained results have been compared to the others achieved by different approaches in the field and the benefits of the proposed methodology have been emphasized. The inference engine of the heuristic algorithms has been presented and the expert system knowledge-base construction discussed.

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Authors and Affiliations

Andrzej Pułka
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Abstract

The main aim of this research is to compare the results of the study of demand’s plan and

standardized time based on three heuristic scheduling methods such as Campbell Dudek

Smith (CDS), Palmer, and Dannenbring. This paper minimizes the makespan under certain

and uncertain demand for domestic boxes at the leading glass company industry in Indonesia.

The investigation is run in a department called Preparation Box (later simply called PRP)

which experiences tardiness while meeting the requirement of domestic demand. The effect

of tardiness leads to unfulfilled domestic demand and hampers the production department

delivers goods to the customer on time. PRP needs to consider demand planning for the

next period under the certain and uncertain demand plot using the forecasting and Monte

Carlo simulation technique. This research also utilizes a work sampling method to calculate

the standardized time, which is calculated by considering the performance rating and

allowance factor. This paper contributes to showing a comparison between three heuristic

scheduling methods performances regarding a real-life problem. This paper concludes that

the Dannenbring method is suitable for large domestic boxes under certain demand while

Palmer and Dannenbring methods are suitable for large domestic boxes under uncertain

demand. The CDS method is suitable to prepare small domestic boxes for both certain and

uncertain demand.

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Authors and Affiliations

Filscha Nurprihatin
Ester Lisnati Jayadi
Hendy Tannady
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Abstract

In the article, the authors propose a typology of political knowledge from online learning activities and test its validity in an empirical qualitative study. The essence of their proposal is that meaningful study of the process of acquiring knowledge (rational analysis of factors modifying attitudes) must take into account both the perspective of the citizen (the demand for information) and an analysis of the publicly available knowledge (the supply of information). The authors distinguish three main methods of acquiring information: heuristic, reflective, and by-product learning. They note the importance of generational factors in shaping the cognitive activity of Internet users. There has been a gradual increase in the importance of source management, with simultaneous alienation and skepticism towards information obtained on the Internet. While the authors’ analysis is restricted to the Internet, their approach is not reductionist in that they consider the internet to be a medium for traditional media and its influence on civic attitudes.

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Authors and Affiliations

Michał Wenzel
Maciej Kryszczuk
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Abstract

A method of creating production schedules regarding production lines with parallel machines is presented. The production line setup provides for intermediate buffers located between individual stages. The method mostly concerns situations when part of the production machines is unavailable for performance of operations and it becomes necessary to modify the original schedule, the consequence of which is the need to build a new schedule. The cost criterion was taken into account, as the schedule is created with the lowest possible costs regarding untimely completion of products (e.g. fines for delayed product completion). The proposed method is relaxing heuristics, thanks to which scheduling is performed in a relatively short time. This was confirmed by the presented results of computational experiments. These experiments were carried out for the rescheduling of machine parts production.

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Authors and Affiliations

Marek Magiera
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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

The paper presents a novel heuristic procedure (further called the AH Method) to investigate function shape in the direct vicinity of the found optimum solution. The survey is conducted using only the space sampling collected during the optimization process with an evolutionary algorithm. For this purpose the finite model of point-set is considered. The statistical analysis of the sampling quality based upon the coverage of the points in question over the entire attraction region is exploited. The tolerance boundaries of the parameters are determined for the user-specified increase of the objective function value above the found minimum. The presented test-case data prove that the proposed approach is comparable to other optimum neighborhood examination algorithms. Also, the AH Method requires noticeably shorter computational time than its counterparts. This is achieved by a repeated, second use of points from optimization without additional objective function calls, as well as significant repository size reduction during preprocessing.
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Authors and Affiliations

Daniel Andrzej Piętak
1
Piotr Bilski
1
ORCID: ORCID
Paweł Jan Napiórkowski
2

  1. Institute of Radioelectronics and Multimedia Technology, Warsaw University of Technology, Poland
  2. Heavy Ion Laboratory, University of Warsaw, Poland
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Abstract

Despite many years of development in the field of rotor dynamics, many issues still need to be resolved. This is due to the fact that turbomachines, even those with low output power, have a very complex design. The author of this article would like to signal these issues in the form of several questions, to which there are no precise answers. The questions are as follows: How can we build a coherent dynamic model of a turbomachine whose some subsystems have non-linear characteristics? How can we consider the so-called prehistory in our analysis, namely, the relation between future dynamic states and previous ones? Is heuristic modelling the future of rotor dynamics? What phenomena may occur when the stability limit of the system is exceeded? The attempt to find answers to these questions constitutes the subject of this article. There are obviously more similar questions, which encourage researchers from all over the world to further their research.
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Bibliography

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  7.  H. Engel, “Berechung der Strömung, der Drücke und Temperaturen in Radial-Axialbund-Gleitlagern mit Hilfe eines Finite-Elemente-Programms,” Ph.D. thesis, Universität Stuttgart, 1992.
  8.  T. Hagemann, H. Blumenthal, C. Kraft, and H. Schwarze, “A study on energetic and hydraulic interaction of combined journal and thrust bearings,” in Proceedings of ASME Turbo Expo 2015: Turbine Technical Conference and Exposition, no. GT2015‒43460, 2015, pp. 1–11.
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  11.  J.-C. Luneno, “Coupled vibrations in horizontal and vertical rotor-bearings systems,” Ph.D. thesis, Luleå University of Technology, 2010.
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  13.  H.G. Elrod, “A cavitation algorithm,” J. Tribol., vol. 103, no. 3, pp. 350–354, 1981.
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  15.  S. Nitzschke, “Instationäres Verhalten schwimmbuchsengelagerter Rotoren unter Berücksichtigung masseerhaltender Kavitation,” Ph.D. thesis, Otto-von-Guericke Universität Magdeburg, 2016.
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  19.  “MAN turbochargers TCA series floating disk thrust bearing,” https://turbocharger.man-es.com/docs/default-source/ shopwaredocuments/ tca-turbochargerf451d068cde04720bdc9b 8e95b7c0f8e.pdf, accessed: 2020‒10‒09.
  20.  “KBB turbochargers ST27 series f loating disk thrust bearing,” https://kbb-turbo.com/turbocharger-product-series/st27-series, accessed: 2020-10-09.
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Authors and Affiliations

Jan Kiciński
1

  1. Institute of Fluid-Flow Machinery, Polish Academy of Sciences, ul. Fiszera 14, Gdańsk 80-231, Poland
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Abstract

The Bulletin of the Polish Academy of Sciences: Technical Sciences (Bull.Pol. Ac.: Tech.) is published bimonthly by the Division IV Engineering Sciences of the Polish Academy of Sciences, since the beginning of the existence of the PAS in 1952. The journal is peer‐reviewed and is published both in printed and electronic form. It is established for the publication of original high quality papers from multidisciplinary Engineering sciences with the following topics preferred: Artificial and Computational Intelligence, Biomedical Engineering and Biotechnology, Civil Engineering, Control, Informatics and Robotics, Electronics, Telecommunication and Optoelectronics, Mechanical and Aeronautical Engineering, Thermodynamics, Material Science and Nanotechnology, Power Systems and Power Electronics.

Journal Metrics: JCR Impact Factor 2018: 1.361, 5 Year Impact Factor: 1.323, SCImago Journal Rank (SJR) 2017: 0.319, Source Normalized Impact per Paper (SNIP) 2017: 1.005, CiteScore 2017: 1.27, The Polish Ministry of Science and Higher Education 2017: 25 points.

Abbreviations/Acronym: Journal citation: Bull. Pol. Ac.: Tech., ISO: Bull. Pol. Acad. Sci.-Tech. Sci., JCR Abbrev: B POL ACAD SCI-TECH Acronym in the Editorial System: BPASTS.

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Authors and Affiliations

Md Musabbir Hossain
Asatur Zh. Khurshudyan
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Abstract

The constrained averaged controllability of linear one-dimensional heat equation defined on R and R+ is studied. The control is carried out by means of the time-dependent intensity of a heat source located at an uncertain interval of the corresponding domain, the end-points of which are considered as uniformly distributed random variables. Employing the Green’s function approach, it is shown that the heat equation is not constrained averaged controllable neither in R nor in R+. Sufficient conditions on initial and terminal data for the averaged exact and approximate controllabilities are obtained. However, constrained averaged controllability of the heat equation is established in the case of point heat source, the location of which is considered as a uniformly distributed random variable. Moreover, it is obtained that the lack of averaged controllability occurs for random variables with arbitrary symmetric density function.

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Authors and Affiliations

Jerzy Klamka
Asatur Zh. Khurshudyan
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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

This paper presents the modeling and the resolution of a two dimensional cutting stock problem for a wooden industry. It is about a real problem of minimization of the wood wastes for an industry of furnishing. The raw material to be cut is a set of beams of various sizes. The purpose of the cut is to supply a list of orders characterized by a set of articles of various sizes. The problem is converted into an integer linear program where the decision variables are the numbers of beams to cut according to a set of feasible “patterns”. The designed solution is a heuristic in two stages: – Generation of the feasible patterns by various classic heuristics of the Bin-packing Problem. – Resolution of the integer linear program with the generated patterns as input variables. Moreover, based on this approach, the “Application Cutting Optimization” is developed to allow the immediate resolution of the problem and widening the stock management horizon. To end, a real case is studied to confirm the effectiveness of this approach.
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Authors and Affiliations

Amine Bouaine
Maria Lebbar
Mohamed Ait Ha
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Abstract

The demand for energy on a global scale increases day by day. Unlike renewable energy sources, fossil fuels have limited reserves and meet most of the world’s energy needs despite their adverse environmental effects. This study presents a new forecast strategy, including an optimization-based S-curve approach for coal consumption in Turkey. For this approach, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), and Whale Optimization Algorithm (WOA) are among the meta-heuristic optimization techniques used to determine the optimum parameters of the S-curve. In addition, these algorithms and Artificial Neural Network (ANN) have also been used to estimate coal consumption. In evaluating coal consumption with ANN, energy and economic parameters such as installed capacity, gross generation, net electric consumption, import, export, and population energy are used for input parameters. In ANN modeling, the Feed Forward Multilayer Perceptron Network structure was used, and Levenberg-Marquardt Back Propagation has used to perform network training. S-curves have been calculated using optimization, and their performance in predicting coal consumption has been evaluated statistically. The findings reveal that the optimization-based S-curve approach gives higher accuracy than ANN in solving the presented problem. The statistical results calculated by the GWO have higher accuracy than the PSO, WOA, and GA with R 2 = 0.9881, RE = 0.011, RMSE = 1.079, MAE = 1.3584, and STD = 1.5187. The novelty of this study, the presented methodology does not need more input parameters for analysis. Therefore, it can be easily used with high accuracy to estimate coal consumption within other countries with an increasing trend in coal consumption, such as Turkey.
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Authors and Affiliations

Mustafa Seker
1
ORCID: ORCID
Neslihan Unal Kartal
2
Selin Karadirek
3
Cevdet Bertan Gulludag
3

  1. Sivas Cumhuriyet University, Turkey
  2. Burdur Mehmet Akif Ersoy University, Turkey
  3. Akdeniz University, Antalya, Turkey
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Abstract

The effective implementation of new market strategies presents the mining enterprises with new challenges which require precise assessment instruments of the carried out business to be met at the level of mines, preparation plants, coking plants, and steelworks. These instruments include deposit, technological, and economic parameters, which together with a safety margin, determining the percentage reserve level of each parameter, shape the profitability of undertaken projects. The paper raises the issue of designing an IT architecture of the system for deposit modelling and mining production scheduling, implemented in the JSW SA. The development and application of the system was important with regard to the overriding objective of the Quality ProgramProgram of the JSW Capital Group, which is increasing the effectiveness of deposit and commercial product quality management. The paper also presents the required specification of the technical architecture necessary to implement systems and the actions required to integrate them with other IT systems of the JSW Group. The heuristic technical architecture of the JSW SA production line management system presented in the paper enables an analysis of the production process profitability in a carried account system in the area of mines, preparation plants, and coking plants of the mining group of the biggest European coal producer for metallurgical purposes.
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Authors and Affiliations

Artur Dyczko
1
ORCID: ORCID

  1. Mineral and Energy Economy Research Institute, Polish Academy of Sciences, Kraków, Poland
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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 deals with the issue of production scheduling for various types of employees in a large manufacturing company where the decision-making process was based on a human factor and the foreman’s know-how, which was error-prone. Modern production processes are getting more and more complex. A company that wants to be competitive on the market must consider many factors. Relying only on human factors is not efficient at all. The presented work has the objective of developing a new employee scheduling system that might be considered a particular case of the job shop problem from the set of the employee scheduling problems. The Neuro-Tabu Search algorithm and the data gathered by manufacturing sensors and process controls are used to remotely inspect machine condition and sustainability as well as for preventive maintenance. They were used to build production schedules. The construction of the Neuro-Tabu Search algorithm combines the Tabu Search algorithm, one of the most effective methods of constructing heuristic algorithms for scheduling problems, and a self-organizing neural network that further improves the prohibition mechanism of the Tabu Search algorithm. Additionally, in the paper, sustainability with the use of Industry 4.0 is considered. That would make it possible to minimize the costs of employees’ work and the cost of the overall production process. Solving the optimization problem offered by Neuro-Tabu Search algorithm and real-time data shows a new way of production management.
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Authors and Affiliations

Anna Burduk
1
ORCID: ORCID
Kamil Musiał
1
Artem Balashov
1
Andre Batako
2
Andrii Safonyk
3
ORCID: ORCID

  1. Wroclaw University of Science and Technology, Faculty of Mechanical Engineering, Wybrzeże Wyspiańskiego 27, 50-370 Wrocław, Poland
  2. Liverpool John Moores University, Faculty of Engineering and Technology,70 Mount Pleasant Liverpool L3 3AF, UK
  3. National University of Water and Environmental Engineering, Department of Automation, Electrical Engineering and Computer-Integrated Technologies, Rivne 33000, Ukraine
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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

Appropriate product categorization in distribution centres is important for business success because of the possibility of intuitive product finding by the picker and increased product movement. Both of these factors result in the operational efficiency of the distribution centre. The goal of this paper is to explore a model of shelf space dimensioning of storage location on a rack with vertical and horizontal product categorization in a distribution centre, where the aim is to increase total product movement/profit from all shelves of the rack. This is controlled by a packer who must complete orders by getting the goods from shelves and picking them to the container. In this problem, we develop two heuristics and compare the archived results to the CPLEX solver. The average profit ratios of both heuristics are high and approximately equal to 99%. In 10 cases, optimal solutions have been found by heuristics.
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Authors and Affiliations

Kateryna Czerniachowska
1
ORCID: ORCID
Radosław Wichniarek
2
ORCID: ORCID
Krzysztof Żywicki
2
ORCID: ORCID

  1. Wroclaw University of Economics and Business, Wroclaw, Poland
  2. Poznan University of Technology, Poznan, Poland
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Abstract

Distribution centres are the important elements of modern supply chains. A distribution centre stores and ships products. In this paper, we investigate the model of the dimensioning of shelf space on the rack with vertical and horizontal product categorisation in a distribution centre, where the objective is to maximise the total product movement/profit from all shelves of the rack which is being managed by a packer who needs to complete orders selecting the products from the shelves and picking them to the container. We apply two newly developed heuristics to this problem and compare the results to the optimal solution found by the CPLEX solver. There are 8 steering parameters that allow for reducing the search space implemented in heuristics. Among them are parameters that decrease the number of products on the shelves, the category with a range for assigning most space for the most profitable products within the category; two versions of steering parameters for the number of generated product allocations, the step parameters for the intensity of solution diversification, and the movement/profit below which the solutions are not generated. The computational results are presented and indicate that higher-quality solutions can be obtained using the new heuristics. In 10 from 15 tests, both heuristics can find optimal solutions without exploring the whole solution space. For the rest test sets, the solutions received by heuristics are not less than 92.58%.
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Authors and Affiliations

Kateryna Czerniachowska
1
ORCID: ORCID
Radosław Wichniarek
2
ORCID: ORCID
Krzysztof Żywicki
2
ORCID: ORCID

  1. Wroclaw University of Economics and Business, Wroclaw, Poland
  2. Poznan University of Technology, Poznan, Poland
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Abstract

The present paper describes a methodological framework developed to select a multi-label dataset transformation method in the context of supervised machine learning techniques. We explore the rectangular 2D strip-packing problem (2D-SPP), widely applied in industrial processes to cut sheet metals and paper rolls, where high-quality solutions can be found for more than one improvement heuristic, generating instances with multi-label behavior. To obtain single-label datasets, a total of five multi-label transformation methods are explored. 1000 instances were generated to represent different 2D-SPP variations found in real-world applications, labels for each instance represented by improvement heuristics were calculated, along with 19 predictors provided by problem characteristics. Finally, classification models were fitted to verify the accuracy of each multi-label transformation method. For the 2D-SPP, the single-label obtained using the exclusion method fit more accurate classification models compared to the other four multi-label transformation methods adopted.
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Authors and Affiliations

Neuenfeldt Júnior Alvaro
Matheus Francescatto
Gabriel Stieler
David Disconzi

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