The object of Master Thesis is the creation and research optimization of blank realization procedures. Four main parts comprise the thesis: analysis of the problem, theoretical solutions, research and outcomes, conclusions and recommendations. Optimization methods, their advantages and limitations have been analyzed in the first part. The most appropriate optimization method for problem solving was selected. Designed optimization methods have been presented in the theoretical solutions part: exhaustive search, tabu search and a new one, presented by the author. A program was created for comparison of these methods. In the third part of the thesis outcomes of the research are presented. Designed methods were tested and compared by their routes length, process time, computations duration and other parameters. Conclusions of the thesis and recommendations for implementation of analyzed procedures have been presented in the part of conclusions. Literature in Lithuanian, English was used in preparing the thesis. There are 19 tables and 29 pictures in the thesis.

Visuomenė, internetas ir jame esanti informacija dabar turi vieną didžiausių įtakų mūsų asmeniniame gyvenime. Be interneto daugelis dabar, net nebeįsivaizduotų savo kasdienybės, nes jis mums ir padeda atlikti daugelį darbų. Tačiau vis augant duomenų kiekiams internete, informacijos paieška tampa vienu svarbiausių internete naudojamų funkcijų.Paieškos sistemos – tai sistemos, ieškančios dokumentų žiniatinklyje, naujienų grupių archyvuose, FTP saugyklose, kuriuos rado paieškos serveris ir įtraukė į savo duomenų bazes. Ieškant informacijos, vartotojai naudojasi šiomis sistemomis, todėl internetinių svetainių kūrėjai yra suinteresuoti, kad jų internetiniai puslapiai būti kuo dažniau randami paieškos sistemų. Todėl besiplečiant paieškos sistemoms išsiplėtojo SEO (Search Engine Optimization, lietuviškai „Optimizavimas paieškos sistemoms“). / Expansion of the Internet and the information contained therein formed such an organization which aims to help the internet users to quickly and efficiently find what he needs. One of them is the Google search engine. It is one of the largest search engine companies in the world. In this paper we will analyse the Google search engine, and its proposed content optimization methods, which it claims to helps achieve better search results positions. The paper will discuss techniques such as HTML meta tags, content headers, site maps, robots.txt file, canonical and Paging functions. These methods will be compared with each other, and we will decide which method is most useful for site optimization.

This paper investigates three methods of one variable function optimizing methods, executes the comparison of their efficiency and generalizes the results of this research. At first there is a review of historical aspects of optimization theory, definition of optimization concept, introduction to task formulation. Presentation of optimization importance, the role of objective function in the process of optimization. Introduction to the classification of optimization tasks and optimization of various systems. In this paper there is an analysis of three methods of optimization: “Half distribution”, “Golden cut”, “Powell”. There was created a program for calculating and comparing of the selected optimization methods. During the investigation it was determined that when there is a small precision (0,1; 0,01), the change of minimum of the function and the value of that point are great. When you increase the value of precision the change of minimum of the function and the value of that point are very small. When the precision value is about (0,0001 .. 0,000001) there is a difference in only 6-th – 9-th value after the comma. The use of “Powell” method requires least steps of calculating, the use of “Half distribution” method requires mostly steps of calculating. In about 80 % of calculation the shortest interval of the search was using the “Powell” method of optimizing, in 20 % of calculation the shortest interval of the search was using the “Golden cut” method of optimization... [to full text]

The problem of profiled school scheduling is important for Lithuanian schools and for similar schools in many other countries. No polynomial time methods are known for this problem. The objective of this PhD thesis is to investigate heuristic methods for optimization of profiled school schedules. The convenience of application in real-life situations is provided by the vector optimization approach using platform-independent software implementation. The task of experimental investigation is to select such parameters of heuristic methods that minimize expected deviation from the optimum. Four optimization methods were regarded: Local Deterministic (LD), Local Randomized (LR), Simulated Annealing (SA), and SA with parameters optimized using the Bayesian approach (BA). The composite method of AM and BA provided the best results. In Chapter 1 of the dissertation, various aspects of work of optimization methods as well as popular program languages suitable for school schedule optimization are analyzed. Literature about school scheduling is analysed. In Chapter 2, conclusions are drawn how the optimization of heuristic parameters influences the speed and accuracy of finding the optimal solution. A technical rating analysis of popular schedule programs is made and technical disadvantages are listed. Criteria for evaluating the quality of results are proposed that include heuristic parameters in search of optimal schedules. Recommendations are states how to assess the choice and... [to full text] / Profiliuotos mokyklos tvarkaraščio kūrimas yra aktualus uždavinys tiek Lietuvoje, tiek kitose šalyse. Nėra žinoma polinominių būdų šiai problemai spręsti. Pagrindinis šios daktaro disertacijos objektas yra ištirti euristinius metodus, skirtus profiliuotos mokyklos tvarkaraščio optimizavimui. Tvarkaraščio formavimo kriterijai, kurie yra reikalingi realiame gyvenime, nustatomi vektorinio optimizavimo metodais bei realizuojami nuo operacinės sistemos nepriklausoma programine įranga. Eksperimentinių tyrimų uždavinys – surasti tokius euristinių metodų parametrus, kurie minimizuotų numatytą nuokrypį. Disertacijoje aprašomi keturi optimizavimo metodai: lokalus determinuotas (LD), lokalus atsitiktinis (LA), atkaitinimo modeliavimo (AM) ir AM parametrų optimizavimas naudojant Bayes (BA) metodą. Kombinuotas AM ir Bayes metodas duoda geriausius rezultatus. Pirmajame apžvelgiama su mokyklos tvarkaraščių formavimu susijusi literatūra. Analizuojami tinkamiausi optimizavimo metodų darbo aspektai. Analizuojamos populiariausios programavimo kalbos, tinkančios kurti mokyklų tvarkaraščių optimizavimo programą. Antrajame skyriuje formuluojamas profiliuotų mokyklų tvarkaraščio kūrimo matematinis modelis. Analizuojami profiliuotose mokyklose naudojami euristiniai parametrai. Atlikti populiarių tvarkaraščių programų vertinimai ir analizės. Įvardijami šių programų trūkumai. Trečiajame skyriuje, remiantis 2 skyriaus analize ir išvadomis, pateiktas profiliuotos mokyklos lanksčios tvarkaraščio... [toliau žr. visą tekstą]

Profiliuotos mokyklos tvarkaraščio kūrimas yra aktualus uždavinys tiek Lietuvoje, tiek kitose šalyse. Nėra žinoma polinominių būdų šiai problemai spręsti. Pagrindinis šios daktaro disertacijos objektas yra ištirti euristinius metodus, skirtus profiliuotos mokyklos tvarkaraščio optimizavimui. Tvarkaraščio formavimo kriterijai, kurie yra reikalingi realiame gyvenime, nustatomi vektorinio optimizavimo metodais bei realizuojami nuo operacinės sistemos nepriklausoma programine įranga. Eksperimentinių tyrimų uždavinys – surasti tokius euristinių metodų parametrus, kurie minimizuotų numatytą nuokrypį. Disertacijoje aprašomi keturi optimizavimo metodai: lokalus determinuotas (LD), lokalus atsitiktinis (LA), atkaitinimo modeliavimo (AM) ir AM parametrų optimizavimas naudojant Bayes (BA) metodą. Kombinuotas AM ir Bayes metodas duoda geriausius rezultatus. Pirmajame apžvelgiama su mokyklos tvarkaraščių formavimu susijusi literatūra. Analizuojami tinkamiausi optimizavimo metodų darbo aspektai. Analizuojamos populiariausios programavimo kalbos, tinkančios kurti mokyklų tvarkaraščių optimizavimo programą. Antrajame skyriuje formuluojamas profiliuotų mokyklų tvarkaraščio kūrimo matematinis modelis. Analizuojami profiliuotose mokyklose naudojami euristiniai parametrai. Atlikti populiarių tvarkaraščių programų vertinimai ir analizės. Įvardijami šių programų trūkumai. Trečiajame skyriuje, remiantis 2 skyriaus analize ir išvadomis, pateiktas profiliuotos mokyklos lanksčios tvarkaraščio... [toliau žr. visą tekstą] / The problem of profiled school scheduling is important for Lithuanian schools and for similar schools in many other countries. No polynomial time methods are known for this problem. The objective of this PhD thesis is to investigate heuristic methods for optimization of profiled school schedules. The convenience of application in real-life situations is provided by the vector optimization approach using platform-independent software implementation. The task of experimental investigation is to select such parameters of heuristic methods that minimize expected deviation from the optimum. Four optimization methods were regarded: Local Deterministic (LD), Local Randomized (LR), Simulated Annealing (SA), and SA with parameters optimized using the Bayesian approach (BA). The composite method of AM and BA provided the best results. In Chapter 1 of the dissertation, various aspects of work of optimization methods as well as popular program languages suitable for school schedule optimization are analyzed. Literature about school scheduling is analysed. In Chapter 2, conclusions are drawn how the optimization of heuristic parameters influences the speed and accuracy of finding the optimal solution. A technical rating analysis of popular schedule programs is made and technical disadvantages are listed. Criteria for evaluating the quality of results are proposed that include heuristic parameters in search of optimal schedules. Recommendations are states how to assess the choice and... [to full text]