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Ordering of Jobs for Pickling Lines
Plšek, Michal ; Tinka, Jan (referee) ; Kanich, Ondřej (advisor)
This work resolves the scheduling problem of multiple hoists transporting products between chemicals baths of pickling line. Harmonograms of products are calculated by modified Shifting bottleneck heuristic, which prevents product conflicts inside baths. Genetic algorithm NSGA-II is used for solution-space search. Web application built over the optimization process allows user to manage/edit products, hoists, baths, configuration parameters and optimization results. Applying proposed heuristic to smaller optimization tasks boosts production effectivity up to 30-45 % (comparing to naive harmonograms). The result of this work is application on the basis of which full-fledged C++ application might be programmed. Then it might be used for solving larger-scale problems.
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Modern methods for intersection signaling control
Bartoš, Pavel ; Lacko, Branislav (referee) ; Kůdela, Jakub (advisor)
This diploma thesis deals with the optimal control of traffic lights at intersections. In the introduction, concepts are introduced and control methods are presented. Subsequently, Eclipse's SUMO software is chosen to create the model. Following the model of a real intersection, both layout and logic and traffic flows are created. The traffic flows itself are partially randomized. The control is performed using three green queue lengths and the evaluation is done by comparing the average and maximum waiting times. Pareto optimal points are thus selected. The first algorithm to obtain the optimal setting is a grid search. The second algorithm has been implemented by NSGA-II. The settings are compared with each other as well as with respect to the settings and the time window.
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Application of Approximate Computing in Image Processing
Hruda, Petr ; Vašíček, Zdeněk (referee) ; Bidlo, Michal (advisor)
This master thesis focuses on approximate computing applied to image processing. Specifically, the approximation is applied to adaptive thresholding. Two approaches were used, the design of a new system using approximated components and the approximation of an existing algorithm. The resulting effect on thresholding quality was investigated. Experimental evaluation of the first approach shows quality improvements of thresholding with usage of aproximated components. Also, area of found aproximated solutions is smaller. Evaluation of the second approach shows worse quality of thresholding with usage of aproximated components. The second approach is then declared inappropriate.
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Implementation of an evolutionary expert system
Bukáček, Jan ; Müller, Jakub (referee) ; Karásek, Jan (advisor)
This thesis is focused on working up evolutionals and genetics algorithms issues Especially for multiobjective algorithms VEGA, SPEA and NSGA – II. Thereinafter one of FrameWork working with genetics algorithms namely WWW NIMBUS. From this mentioned algorithms was selected VEGA algorithm for implementation in JAVA to preselected problem. Thereby problem is choice thick columns of profile according to predetermined criteria. Selected algorithm works on division of population into several groups and each group evaluates the resulting fitness function. Here is a sample implementation of this algorithm. Furthermore there is a example of working with FrameWork. In the next section are compared the results of generated progam with results that were obtained by FrameWork WWW NIMBUS. As for VEGA, and the Nimbus there are shown different results. The VEGA is presented also the development of individual fitness functions. Also, there are shown graphs, that can be obtained from NIMBUS. At the end of work is introduced the comparation of the results ane propose possible improvements.
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Processes Supporting Decision-Making
Križan, Viliam ; Uher, Václav (referee) ; Karásek, Jan (advisor)
This thesis deals with algorithms for supporting decision processes. Firstly, Analytic Hierachy Process (AHP) and Analytic Network Process (ANP) developed by prof. Thomas L. Saaty are described. Basic principles and the implementation in Java programing language of the decision processes are explained. Both processes are then analyzed and their pros and cons and also practical aspect are explained. Secondly, the genetic algorithm NSGA-II developed by Kalyanmoy Deb is described. There are also basic principles and implementation in Java programing language explained. There are finaly the results of NSAG-II algorithm presented.
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Toolbox for multi-objective optimization
Marek, Martin ; Hurák,, Zdeněk (referee) ; Kadlec, Petr (advisor)
This paper deals with multi-objective optimization problems (MOOP). It is explained, what solutions in multi-objetive search space are optimal and how are optimal (non-dominated) solutions found in the set of feasible solutions. Afterwards, principles of NSGA-II, MOPSO and GDE3 algorithms are described. In the following chapters, benchmark metrics and problems are introduced. In the last part of this paper, all the three algorithms are compared based on several benchmark metrics.
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Evolutionary Design of EEG Data Classifier
Kuželová, Simona ; Jawed, Soyiba (referee) ; Mrázek, Vojtěch (advisor)
Tato diplomová práce se zaměřuje na vývoj efektivního klasifikátoru pro klasifikaci kandidátů na základě extrahovaných vlastností z elektroencefalografického (EEG) signálu. K dosažení tohoto cíle byl použit genetický algoritmus pro výběr příznaků a optimalizaci klasifikátorů na základě pěti kritérií: minimalizace počtu příznaků, minimalizace doby inference a maximalizace klasifikační senzitivity, specificity a přesnosti. Pro extrakci příznaků s cílem klasifikovat kandidáty jako trpící MDD, nebo jako zdravé, byla použita EEG data s otevřenýma očima 31 kandidátů trpících depresivní poruchou (MDD) a 28 zdravých kandidátů. Byly otestovány dva algoritmy, NSGA-II a NSGA-III. Navržený algoritmus pracoval se třemi kritérii, ale byly přidány dvě další kritéria - senzitivita a specificita. NSGA-III byl v tomto případě účinnější a byl použit v následujících experimentech. Byla zavedena omezení pro zlepšení parametrů a byly vyzkoušeny různé hodnoty pro pravděpodobnost mutace a křížení. Vygenerované klasifikátory dosáhly průměrné přesnosti 91.36 \%, senzitivity 91.82 \% a specificity 90.84 \%. V závěrečných experimentech byly nejčastěji používány kanály F3 a C3 a nejčastěji využívaným vlnovým pásmem byla gama frekvence. Výsledkem této práce jsou efektivní klasifikátory, které byly získány pomocí navrženého algoritmu, jenž využívá genetický algoritmus pro optimalizaci parametrů.
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Modern methods for intersection signaling control
Bartoš, Pavel ; Lacko, Branislav (referee) ; Kůdela, Jakub (advisor)
This diploma thesis deals with the optimal control of traffic lights at intersections. In the introduction, concepts are introduced and control methods are presented. Subsequently, Eclipse's SUMO software is chosen to create the model. Following the model of a real intersection, both layout and logic and traffic flows are created. The traffic flows itself are partially randomized. The control is performed using three green queue lengths and the evaluation is done by comparing the average and maximum waiting times. Pareto optimal points are thus selected. The first algorithm to obtain the optimal setting is a grid search. The second algorithm has been implemented by NSGA-II. The settings are compared with each other as well as with respect to the settings and the time window.
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Ordering of Jobs for Pickling Lines
Plšek, Michal ; Tinka, Jan (referee) ; Kanich, Ondřej (advisor)
This work resolves the scheduling problem of multiple hoists transporting products between chemicals baths of pickling line. Harmonograms of products are calculated by modified Shifting bottleneck heuristic, which prevents product conflicts inside baths. Genetic algorithm NSGA-II is used for solution-space search. Web application built over the optimization process allows user to manage/edit products, hoists, baths, configuration parameters and optimization results. Applying proposed heuristic to smaller optimization tasks boosts production effectivity up to 30-45 % (comparing to naive harmonograms). The result of this work is application on the basis of which full-fledged C++ application might be programmed. Then it might be used for solving larger-scale problems.
|
|
|
Application of Approximate Computing in Image Processing
Hruda, Petr ; Vašíček, Zdeněk (referee) ; Bidlo, Michal (advisor)
This master thesis focuses on approximate computing applied to image processing. Specifically, the approximation is applied to adaptive thresholding. Two approaches were used, the design of a new system using approximated components and the approximation of an existing algorithm. The resulting effect on thresholding quality was investigated. Experimental evaluation of the first approach shows quality improvements of thresholding with usage of aproximated components. Also, area of found aproximated solutions is smaller. Evaluation of the second approach shows worse quality of thresholding with usage of aproximated components. The second approach is then declared inappropriate.
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