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[nazev] => Commentary on: “STOA: A bio-inspired based optimization algorithm for industrial engineering problems” [EAAI, 82 (2019), 148–174] and “Tunicate Swarm Algorithm: A new bio-inspired based metaheuristic paradigm for global optimization” [EAAI, 90 (2020), no. 103541]
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[popis] => This commentary concerns two recently developed metaheuristic algorithms, namely the Sooty Tern Optimization Algorithm, and the Tunicate Swarm Algorithm. Both of these algorithms claim computational superiority over other methods based on experimental results on a certain benchmark set. The aim of this note is to aware researchers that this claim is not valid: the proposed algorithms use a zero-bias operator and many of the studied benchmark functions on which they were found superior have optimal solutions located in the zero vector. Moreover, the codes for the methods provided by the authors are not achieving the results reported in the respective publications.
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[klicova_slova] => Sooty Tern Optimization; Tunicate Swarm Algorithm; Metaheuristic optimization; Benchmarking
[klicova_slova_orig] => Sooty Tern Optimization; Tunicate Swarm Algorithm; Metaheuristic optimization; Benchmarking
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[citace_text] => KŮDELA, J. Commentary on: “STOA: A bio-inspired based optimization algorithm for industrial engineering problems” [EAAI, 82 (2019), 148–174] and “Tunicate Swarm Algorithm: A new bio-inspired based metaheuristic paradigm for global optimization” [EAAI, 90 (2020), no. 103541]. Engineering Applications of Artificial Intelligence, 2022, vol. 113, no. 1, p. 1-3. ISSN: 0952-1976.
[citace_html] => KŮDELA, J. Commentary on: “STOA: A bio-inspired based optimization algorithm for industrial engineering problems” [EAAI, 82 (2019), 148–174] and “Tunicate Swarm Algorithm: A new bio-inspired based metaheuristic paradigm for global optimization” [EAAI, 90 (2020), no. 103541]. Engineering Applications of Artificial Intelligence, 2022, vol. 113, no. 1, p. 1-3. ISSN: 0952-1976.
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author="Jakub {Kůdela}",
title="Commentary on: “STOA: A bio-inspired based optimization algorithm for industrial engineering problems” [EAAI, 82 (2019), 148–174] and “Tunicate Swarm Algorithm: A new bio-inspired based metaheuristic paradigm for global optimization” [EAAI, 90 (2020), no. 103541]",
journal="Engineering Applications of Artificial Intelligence",
year="2022",
volume="113",
number="1",
pages="1--3",
doi="10.1016/j.engappai.2022.104930",
issn="0952-1976",
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[nazev] => Centroid based person detection using pixelwise prediction of the position
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[popis] => Implementations of person detection in tracking and counting systems tend towards processing of orthogonally captured images on edge computing devices. The ellipse-like shape of heads in orthogonally captured images inspired us to predict head centroids to determine positions of persons in images. We predict the centroids using a fully convolutional network (FCN). We combine the FCN with simple image processing operations to ensure fast inference of the detector. We experiment with the size of the FCN output to further decrease the inference time. We compare the proposed centroid-based detector with bounding box-based detectors on head detection task in terms of the inference time and the detection performance. We propose a performance measure which allows quantitative comparison of the two detection approaches. For the training and evaluation of the detectors, we form original datasets of 8000 annotated images, which are characterized by high variability in terms of lighting conditions, background, image quality, and elevation profile of scenes. We propose an approach which allows simultaneous annotation of the images for both bounding box-based and centroid-based detection. The centroid-based detector shows the best detection performance while keeping edge computing standards.
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[klicova_slova] => Persondetection; Fullyconvolutionalnetworks; Performancemeasure; Edgecomputing; Computervision
[klicova_slova_orig] => Persondetection; Fullyconvolutionalnetworks; Performancemeasure; Edgecomputing; Computervision
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[citace_rtf] =>
[citace_bibtex] => @article{BUT178514,
author="Petr {Doležel} and Pavel {Škrabánek} and Dominik {Štursa} and Bruno {Baruque Zanon} and Hector {Cogollos Adrian} and Pavel {Krýda}",
title="Centroid based person detection using pixelwise prediction of the position",
journal="Journal of Computational Science",
year="2022",
volume="63",
number="1",
pages="1--12",
doi="10.1016/j.jocs.2022.101760",
issn="1877-7503",
url="https://www.sciencedirect.com/science/article/pii/S1877750322001442"
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[nazev] => Recent advances and applications of surrogate models for finite element method computations: a review
[nazev_orig] => Recent advances and applications of surrogate models for finite element method computations: a review
[duvernost_udaju_id] => S
[popis] => The utilization of surrogate models to approximate complex systems has recently gained increased popularity. Because of their capability to deal with black-box problems and lower computational requirements, surrogates were successfully utilized by researchers in various engineering and scientific fields. An efficient use of surrogates can bring considerable savings in computational resources and time. Since literature on surrogate modelling encompasses a large variety of approaches, the appropriate choice of a surrogate remains a challenging task. This review discusses significant publications where surrogate modelling for finite element method-based computations was utilized. We familiarize the reader with the subject, explain the function of surrogate modelling, sampling and model validation procedures, and give a description of the different surrogate types. We then discuss main categories where surrogate models are used: prediction, sensitivity analysis, uncertainty quantification, and surrogate-assisted optimization, and give detailed account of recent advances and applications. We review the most widely used and recently developed software tools that are used to apply the discussed techniques with ease. Based on a literature review of 180 papers related to surrogate modelling, we discuss major research trends, gaps, and practical recommendations. As the utilization of surrogate models grows in popularity, this review can function as a guide that makes surrogate modelling more accessible.
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[klicova_slova] => Surrogate model; Surrogate-assisted optimization; Sensitivity analysis; Uncertainty quantification; Finite element method
[klicova_slova_orig] => Surrogate model; Surrogate-assisted optimization; Sensitivity analysis; Uncertainty quantification; Finite element method
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[citace_text] => KŮDELA, J.; MATOUŠEK, R. Recent advances and applications of surrogate models for finite element method computations: a review. SOFT COMPUTING, 2022, vol. 26, no. 1, p. 13709-13733. ISSN: 1432-7643.
[citace_html] => KŮDELA, J.; MATOUŠEK, R. Recent advances and applications of surrogate models for finite element method computations: a review. SOFT COMPUTING, 2022, vol. 26, no. 1, p. 13709-13733. ISSN: 1432-7643.
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author="Jakub {Kůdela} and Radomil {Matoušek}",
title="Recent advances and applications of surrogate models for finite element method computations: a review",
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year="2022",
volume="26",
number="1",
pages="13709--13733",
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[nazev_en] => Recent advances and applications of surrogate models for finite element method computations: a review
[popis_en] => The utilization of surrogate models to approximate complex systems has recently gained increased popularity. Because of their capability to deal with black-box problems and lower computational requirements, surrogates were successfully utilized by researchers in various engineering and scientific fields. An efficient use of surrogates can bring considerable savings in computational resources and time. Since literature on surrogate modelling encompasses a large variety of approaches, the appropriate choice of a surrogate remains a challenging task. This review discusses significant publications where surrogate modelling for finite element method-based computations was utilized. We familiarize the reader with the subject, explain the function of surrogate modelling, sampling and model validation procedures, and give a description of the different surrogate types. We then discuss main categories where surrogate models are used: prediction, sensitivity analysis, uncertainty quantification, and surrogate-assisted optimization, and give detailed account of recent advances and applications. We review the most widely used and recently developed software tools that are used to apply the discussed techniques with ease. Based on a literature review of 180 papers related to surrogate modelling, we discuss major research trends, gaps, and practical recommendations. As the utilization of surrogate models grows in popularity, this review can function as a guide that makes surrogate modelling more accessible.
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[nazev] => Intelligent Sampling of Anterior Human Nasal Swabs using a Collaborative Robotic Arm
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[popis] => Advanced robotics does not always have to be associated with Industry 4.0, but can also be applied, for example, in the Smart Hospital concept. Developments in this field have been driven by the coronavirus disease (COVID-19), and any improvement in the work of medical staff is welcome. In this paper, an experimental robotic platform was designed and implemented whose main function is the swabbing samples from the nasal vestibule. The robotic platform represents a complete integration of software and hardware, where the operator has access to a web-based application and can control a number of functions. The increased safety and collaborative approach cannot be overlooked. The result of this work is a functional prototype of the robotic platform that can be further extended, for example, by using alternative technologies, extending patient safety, or clinical tests and studies. Code is available at https://github.com/ Steigner/ Robo_ Medicinae_ I.
[popis_orig] => Advanced robotics does not always have to be associated with Industry 4.0, but can also be applied, for example, in the Smart Hospital concept. Developments in this field have been driven by the coronavirus disease (COVID-19), and any improvement in the work of medical staff is welcome. In this paper, an experimental robotic platform was designed and implemented whose main function is the swabbing samples from the nasal vestibule. The robotic platform represents a complete integration of software and hardware, where the operator has access to a web-based application and can control a number of functions. The increased safety and collaborative approach cannot be overlooked. The result of this work is a functional prototype of the robotic platform that can be further extended, for example, by using alternative technologies, extending patient safety, or clinical tests and studies. Code is available at https://github.com/ Steigner/ Robo_ Medicinae_ I.
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[klicova_slova_orig] => Robotics, Smart Hospital, Convolution Neural Network (CNN), U-Net, ASPOCRNet, Robot Operating System (ROS)
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[citace_text] => PARÁK, R.; JUŘÍČEK, M. Intelligent Sampling of Anterior Human Nasal Swabs using a Collaborative Robotic Arm. Mendel Journal series, 2022, vol. 28, no. 1, p. 32-40. ISSN: 1803-3814.
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[citace_rtf] =>
[citace_bibtex] => @article{BUT178840,
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journal="Mendel Journal series",
year="2022",
volume="28",
number="1",
pages="32--40",
doi="10.13164/mendel.2022.1.032",
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[nazev_en] => Intelligent Sampling of Anterior Human Nasal Swabs using a Collaborative Robotic Arm
[popis_en] => Advanced robotics does not always have to be associated with Industry 4.0, but can also be applied, for example, in the Smart Hospital concept. Developments in this field have been driven by the coronavirus disease (COVID-19), and any improvement in the work of medical staff is welcome. In this paper, an experimental robotic platform was designed and implemented whose main function is the swabbing samples from the nasal vestibule. The robotic platform represents a complete integration of software and hardware, where the operator has access to a web-based application and can control a number of functions. The increased safety and collaborative approach cannot be overlooked. The result of this work is a functional prototype of the robotic platform that can be further extended, for example, by using alternative technologies, extending patient safety, or clinical tests and studies. Code is available at https://github.com/ Steigner/ Robo_ Medicinae_ I.
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[nazev_orig] => Ověřená technologie pro WEDM obrábění měděné slitiny Ampcoloy
[duvernost_udaju_id] => S
[popis] => Výstupem bude ověřená technologie v podobě optimálního nastavení parametrů stroje elektroerozivní drátové řezačky pro obrábění měděné slitiny, s níž bude dosaženo zvýšení produktivity výroby v podobě zkrácení strojního času a také dodržení požadovaných parametrů topografie povrchu předepsaných normou VDI 3402Blatt4 na hodnotu 25-35, což umožní snížení přilnavosti povrchu a umožní snížení či plné odstranění užívání separačních sprejů obsluhou vstřikolisu.
[popis_orig] => Výstupem bude ověřená technologie v podobě optimálního nastavení parametrů stroje elektroerozivní drátové řezačky pro obrábění měděné slitiny, s níž bude dosaženo zvýšení produktivity výroby v podobě zkrácení strojního času a také dodržení požadovaných parametrů topografie povrchu předepsaných normou VDI 3402Blatt4 na hodnotu 25-35, což umožní snížení přilnavosti povrchu a umožní snížení či plné odstranění užívání separačních sprejů obsluhou vstřikolisu.
[klicova_slova] => WEDM; Ampcoloy; VDI 3402Blatt4 25-35; optimální nastavení parametrů stroje
[klicova_slova_orig] => WEDM; Ampcoloy; VDI 3402Blatt4 25-35; optimální nastavení parametrů stroje
[url] =>
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[vycet_osob] => DVOŘÁK, J; MOURALOVÁ, K.; BEDNÁŘ, J.; PROKEŠ, T.; ZAHRADNÍČEK, R.
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[citace_text] => DVOŘÁK, J; MOURALOVÁ, K.; BEDNÁŘ, J.; PROKEŠ, T.; ZAHRADNÍČEK, R.: Ověřená technologie pro WEDM obrábění měděné slitiny Ampcoloy. (Ověřená technologie)
[citace_html] => DVOŘÁK, J; MOURALOVÁ, K.; BEDNÁŘ, J.; PROKEŠ, T.; ZAHRADNÍČEK, R.: Ověřená technologie pro WEDM obrábění měděné slitiny Ampcoloy. (Ověřená technologie)
[citace_rtf] =>
[citace_bibtex] => @misc{BUT178992,
author="Kateřina {Mouralová} and Josef {Bednář} and Tomáš {Prokeš} and Radim {Zahradníček}",
title="Ověřená technologie pro WEDM obrábění měděné slitiny Ampcoloy",
year="2022",
note="Verified technology"
}
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[nazev_en] => Proven technology for WEDM machining of Ampcoloy copper alloy
[popis_en] => The output will be a proven technology in the form of an optimal setting of the machine parameters of an electroerosive wire cutter for machining copper alloy, with which an increase in production productivity will be achieved in the form of a reduction in machine time, as well as compliance with the required surface topography parameters prescribed by the VDI 3402Blatt4 standard to a value of 25-35, which will enable a reduction adhesion of the surface and will enable the reduction or complete elimination of the use of separation sprays by the injection molding operator.
[klicova_slova_en] => WEDM; Ampcoloy; VDI 3402Blatt4 25-35; optimal setting of machine parameters
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[popis] => Computer vision systems perform based on their design and parameter setting. In computer vision systems that use grayscale conversion, the conversion of RGB images to a grayscale format influences performance of the systems in terms of both results quality and computational costs. Appropriate setting of the weights for the weighted means grayscale conversion, co-estimated with other parameters used in the computer vision system, helps to approach the desired performance of a system or its subsystem at the cost of a negligible or no increase in its time-complexity. However, parameter space of the system and subsystem as extended by the grayscale conversion weights can contain substandard settings. These settings show strong sensitivity of the system and subsystem to small changes in the distribution of data in a color space of the processed images. We developed a methodology for Tuning of the Grayscale computer Vision systems (TGV) that exploits the advantages while compensating for the disadvantages of the weighted means grayscale conversion. We show that the TGV tuning improves computer vision system performance by up to 16% in the tested case studies. The methodology provides a universally applicable solution that merges the utility of a fine-tuned computer vision system with the robustness of its performance against variable input data.
[popis_orig] => Computer vision systems perform based on their design and parameter setting. In computer vision systems that use grayscale conversion, the conversion of RGB images to a grayscale format influences performance of the systems in terms of both results quality and computational costs. Appropriate setting of the weights for the weighted means grayscale conversion, co-estimated with other parameters used in the computer vision system, helps to approach the desired performance of a system or its subsystem at the cost of a negligible or no increase in its time-complexity. However, parameter space of the system and subsystem as extended by the grayscale conversion weights can contain substandard settings. These settings show strong sensitivity of the system and subsystem to small changes in the distribution of data in a color space of the processed images. We developed a methodology for Tuning of the Grayscale computer Vision systems (TGV) that exploits the advantages while compensating for the disadvantages of the weighted means grayscale conversion. We show that the TGV tuning improves computer vision system performance by up to 16% in the tested case studies. The methodology provides a universally applicable solution that merges the utility of a fine-tuned computer vision system with the robustness of its performance against variable input data.
[klicova_slova] => Computer vision; Parameter optimization; Performance evaluation; WECIA graph; Weighted means grayscale conversion
[klicova_slova_orig] => Computer vision; Parameter optimization; Performance evaluation; WECIA graph; Weighted means grayscale conversion
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[citace_text] => ŠKRABÁNEK, P.; MARTÍNKOVÁ, N. Tuning of grayscale computer vision systems. DISPLAYS, 2022, no. 74, p. 102286-102286. ISSN: 0141-9382.
[citace_html] => ŠKRABÁNEK, P.; MARTÍNKOVÁ, N. Tuning of grayscale computer vision systems. DISPLAYS, 2022, no. 74, p. 102286-102286. ISSN: 0141-9382.
[citace_rtf] =>
[citace_bibtex] => @article{BUT179012,
author="Pavel {Škrabánek} and Natália {Martínková}",
title="Tuning of grayscale computer vision systems",
journal="DISPLAYS",
year="2022",
number="74",
pages="102286--102286",
doi="10.1016/j.displa.2022.102286",
issn="0141-9382",
url="https://www.sciencedirect.com/science/article/pii/S0141938222001044"
}
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[popis_en] => Computer vision systems perform based on their design and parameter setting. In computer vision systems that use grayscale conversion, the conversion of RGB images to a grayscale format influences performance of the systems in terms of both results quality and computational costs. Appropriate setting of the weights for the weighted means grayscale conversion, co-estimated with other parameters used in the computer vision system, helps to approach the desired performance of a system or its subsystem at the cost of a negligible or no increase in its time-complexity. However, parameter space of the system and subsystem as extended by the grayscale conversion weights can contain substandard settings. These settings show strong sensitivity of the system and subsystem to small changes in the distribution of data in a color space of the processed images. We developed a methodology for Tuning of the Grayscale computer Vision systems (TGV) that exploits the advantages while compensating for the disadvantages of the weighted means grayscale conversion. We show that the TGV tuning improves computer vision system performance by up to 16% in the tested case studies. The methodology provides a universally applicable solution that merges the utility of a fine-tuned computer vision system with the robustness of its performance against variable input data.
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[popis] => Standard evolutionary optimization algorithms assume that the evaluation of the objective and constraint functions is straightforward and computationally cheap. However, in many real-world optimization problems, these evaluations involve computationally expensive numerical simulations or physical experiments. Surrogate-assisted evolutionary algorithms (SAEAs) have recently gained increased attention for their performance in solving these types of problems. The main idea of SAEAs is the integration of an evolutionary algorithm with a selected surrogate model that approximates the computationally expensive function. In this paper, we propose a surrogate model based on a Lipschitz underestimation and use it to develop a differential evolution-based algorithm. The algorithm, called Lipschitz Surrogate-assisted Differential Evolution (LSADE), utilizes the Lipschitz-based surrogate model, along with a standard radial basis function surrogate model and a local search procedure. The experimental results on seven benchmark functions of dimensions 30, 50, 100, and 200 show that the proposed LSADE algorithm is competitive compared with the state-of-the-art algorithms under a limited computational budget, being especially effective for the very complicated benchmark functions in high dimensions.
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[nazev] => A critical problem in benchmarking and analysis of evolutionary computation methods
[nazev_orig] => A critical problem in benchmarking and analysis of evolutionary computation methods
[duvernost_udaju_id] => S
[popis] => Benchmarking constitutes a cornerstone in the analysis and development of computational methods. Especially in the field of evolutionary computation, where theoretical analysis of the algorithms is almost impossible, benchmarking is at the center of attention. In this text, we show that some of the frequently used benchmark functions that have their respective optima in the center of the feasible set pose a critical problem for the analysis of evolutionary computation methods. We carry out the analysis of seven recent methods, published in respected journals, which contain a center-bias operator that lets them find these optima with ease. This makes their comparison with other methods (that do not have a center-bias) meaningless on such types of problems. We perform a computational comparison of these methods with two of the oldest methods in evolutionary computation on shifted problems and on more advanced benchmark problems. The results show a serious problem, as only one of the seven methods performed consistently better than the pair of old methods, three performed on par, two performed very badly, and the worst one performed barely better than a random search. We also give several suggestions that could help to resolve the presented issues.
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[klicova_slova] => Evolutionary computation; Metaheuristics; Benchmarking; Zero-bias
[klicova_slova_orig] => Evolutionary computation; Metaheuristics; Benchmarking; Zero-bias
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[citace_text] => KŮDELA, J. A critical problem in benchmarking and analysis of evolutionary computation methods. Nature Machine Intelligence, 2022, no. 4, p. 1238-1245. ISSN: 2522-5839.
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[nazev_orig] => The Assignment Problem and Its Relation to Logistics Problems
[duvernost_udaju_id] => S
[popis] => The assignment problem is a problem that takes many forms in optimization and graph theory, and by changing some of the constraints or interpreting them differently and adding other constraints, it can be converted to routing, distribution and scheduling problems. Showing such correlations is one of the aims of this paper. Some of the derived problems having exponential time complexity, the question arises of their solvability for larger instances. Instead of the traditional approach based on the use of approximate or stochastic heuristic methods, we focus here on the direct use of mixed integer programming models in the GAMS environment, which is now capable of solving instances much larger than in the past and does not require complex parameter settings or statistical evaluation of the results as in the case of stochastic heuristics because the computational core of software tools, nested in GAMS, is deterministic in nature. The source codes presented may be an aid, because this tool is not yet as well known as the MATLAB Optimisation Toolbox. Benchmarks of the permutation flow shop scheduling problem with informally derived MIP model and the travelling salesman problem are used to present the limits of the software’s applicability.
[popis_orig] => The assignment problem is a problem that takes many forms in optimization and graph theory, and by changing some of the constraints or interpreting them differently and adding other constraints, it can be converted to routing, distribution and scheduling problems. Showing such correlations is one of the aims of this paper. Some of the derived problems having exponential time complexity, the question arises of their solvability for larger instances. Instead of the traditional approach based on the use of approximate or stochastic heuristic methods, we focus here on the direct use of mixed integer programming models in the GAMS environment, which is now capable of solving instances much larger than in the past and does not require complex parameter settings or statistical evaluation of the results as in the case of stochastic heuristics because the computational core of software tools, nested in GAMS, is deterministic in nature. The source codes presented may be an aid, because this tool is not yet as well known as the MATLAB Optimisation Toolbox. Benchmarks of the permutation flow shop scheduling problem with informally derived MIP model and the travelling salesman problem are used to present the limits of the software’s applicability.
[klicova_slova] => assignment problem; travelling salesman problem; vehicle routing problem; flow shop scheduling problem; GAMS, genetic algorithm
[klicova_slova_orig] => assignment problem; travelling salesman problem; vehicle routing problem; flow shop scheduling problem; GAMS, genetic algorithm
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[citace_text] => ŠEDA, M. The Assignment Problem and Its Relation to Logistics Problems. Algorithms, 2022, vol. 15, no. 10, p. 1-27. ISSN: 1999-4893.
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author="Miloš {Šeda}",
title="The Assignment Problem and Its Relation to Logistics Problems",
journal="Algorithms",
year="2022",
volume="15",
number="10",
pages="1--27",
doi="10.3390/a15100377",
url="https://www.mdpi.com/1999-4893/15/10/377"
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[popis_en] => The assignment problem is a problem that takes many forms in optimization and graph theory, and by changing some of the constraints or interpreting them differently and adding other constraints, it can be converted to routing, distribution and scheduling problems. Showing such correlations is one of the aims of this paper. Some of the derived problems having exponential time complexity, the question arises of their solvability for larger instances. Instead of the traditional approach based on the use of approximate or stochastic heuristic methods, we focus here on the direct use of mixed integer programming models in the GAMS environment, which is now capable of solving instances much larger than in the past and does not require complex parameter settings or statistical evaluation of the results as in the case of stochastic heuristics because the computational core of software tools, nested in GAMS, is deterministic in nature. The source codes presented may be an aid, because this tool is not yet as well known as the MATLAB Optimisation Toolbox. Benchmarks of the permutation flow shop scheduling problem with informally derived MIP model and the travelling salesman problem are used to present the limits of the software’s applicability.
[klicova_slova_en] => assignment problem; travelling salesman problem; vehicle routing problem; flow shop scheduling problem; GAMS, genetic algorithm
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