Sparčiai plintant informacinėms technologijoms vis daugiau daiktų ir paslaugų yra perkeliama į virtualią erdvę. Šis darbas nagrinėja galimybę padaryti universaliu rezervacijos procesą. Pagrindinis tikslas sukurti paprastą sistemą, kurią skirtingoms situacijoms galėtų susikonfigūruoti pats vartotojas. Viena iš sudėtingiausių funkcijų kurią nagrinėja darbas yra galimybė sistemai generuoti automatinius tvarkaraščius. Sistemos praktiškumo būtinybė reikalavo gana plataus analizės spektro: sistemos įgyvendinimo principo tyrimo, programinės įrangos parinkimo, rezervavimo algoritmo sukūrimo, tvarkaraščių sudarymo algoritmo išvedimo. Galutinis rezultatas yra ištirti ir aprašyti konfigūravimo, administravimo bei rezervavimo procesai, jų tyrimų metodai ir gauti rezultatai. / With rapid spread of information technologies, more and more things and services are transferred to the virtual space. Online stores or online reservation systems has long ceased to surprise customers. The main purpose of this master thesis is to analyze and find the way to universalize online reservation process using information gathered from scientific literature analysis and from author’s research. The main objective is to create a model of a simple system for the different situations that could be configured by administrator. Since most of internet users have great computer skills and new IT technologies are becoming more sophisticated and easier to use, most of processes could be performed by ordinary user with no IT education with use of simplified tools. One of the most complex parts of this thesis is to examine the possibility of the system to generate automated schedules. Usability of the system called for the need of a relatively broad spectrum of analysis: the research of various ways of implementation of system, software selection, the creation of a reservation algorithm, scheduling algorithm modification and analysis. In my work I analyze theoretical fundamentals needed for creation of sophisticated reservation system. I review installation and configuration, reservation, object creation and other processes. Also I examine real situations and possible their implementation. The final result of my thesis is detailed information about preferred implementation way... [to full text]

In this work was created algorithm of SA – Simulated Annealing method and GMJ – Global Minimizer for Java. GMJ it’s solution of so called frames of optimised tasks. The method of SA is a technique that has attracted significant attention as suitable for optimization problems of large scale. For practical purposes, simulated annealing has effectively “solved” the famous travelling salesman. At the heart of the method of simulated annealing is an analogy with thermodynamics, specifically with the way that liquids freeze and crystallize, or metals cool and anneal. So the essence of the process is slow cooling, allowing ample time for redistribution of the atoms as they lose mobility. This is the technical definition of annealing, and it is essential for ensuring that a low energy state will be achieved. GMJ – it’s a software solution of so called frames of global optimisation tasks. This method realizes: · algorithms of global optimisation (methods), · functions, that’s can be optimised (tasks), · objects, that’s can be showed on display (analysis). After the program was created, exhaustive inquiry of in this work realized methods was done: analysed influence of teachers, students and others different restrains multipliers to school scheduler making. The research was done using the data of college of Marijampolė. There was accomplished theoretical and experimental comparison of SA and the school schedule programs of others firms.

Darbo pradžioje supažindinsiu su gamybinių tvarkaraščių sudarymo uždaviniu. Jo tikslas rasti tvarkaraštį tam tikrai gamybinei situacijai. Uždavinys turi pilnai nusakyti kas ir kur turi įvykti ir apibrėžti visus apribojimus, o gautas sprendinys turi tenkinti šiuos reikalavimus ir vienareikšmiškai nusakyti operacijų vykdymą. Ši problema aktuali gamyklose, personalo valdyme, krovinių gabenime, oro uostuose, traukinių stotyse ir daugelyje kitų. Kadangi matematinis gamybinių tvarkaraščių sudarymo apibūdinimas sudaromas atsižvelgiant į realaus pasaulio problemas, egzistuoja daug šio uždavinio variantų. Dėl to teko pasirinkti kurį konkretų uždavinį nagrinėti. Pirmajame skyriuje supažindinu su šiuo konkrečiu uždaviniu, pateikiu apibrėžimus, s��vokas ir egzistuojančias problemas sprendžiant gamybinių tvarkaraščių uždavinį. Galiausiai parodysiu, kad tai yra sunkiai sprendžiamas ir dėl to vienas iš aktualių kombinatorinio optimizavimo uždavinių. Tuomet plačiau apibūdinu genetinį ir skruzdžių kolonijos optimizavimo algoritmus. Šie algoritmai ir naudojami sprendžiant mano konkret�� gamybinių tvarkaraščių sudarymo uždavinį. Aš apibūdinu visus parametrus ir koeficientus. Vėliau aš pristatau sukurtą programinę įrangą, skirtą rasti spręsti gamybinių tvarkaraščių sudarymo uždavinį ir vaizdžiai pateikti gautus sprendinius. Taip pat grafikų lentelių ir kitų priemonių pagalba pateikiu atliktų eksperimentų rezultatus. Tuomet apžvelgiu gautus rezultatus ir aptariu pastebėtas tendencijas ir... [toliau žr. visą tekstą] / At the begining of this work introduction to the scheduling problem and its basics is given. The goal of a scheduling problem is to make a schedule for a certain production situation. In the problem it is stated what must take place, and the solution describes exactly what should happen at what time. These problems occur in factories, personnel planning, transportation, airfields, railroad stations etcetera. Since mathematical descriptions of scheduling problems are often distilled from practical situations there are many variants of scheduling problems. A selection had to be made which problem is going to be a target of the study. The job shop scheduling problem was chosen. In the first chapter there is definitions of the problems we are trying to solve, introduction of important concepts (properties, bounds, definitions) from the field of scheduling. The last section takes a small detour into theoretical computer science in order to make precise that scheduling problems are hard to solve. In the second chapter introduction of genetic and ant colony optomization algorithms and its basius is given. It is used to solve scheduling problem, which was mentioned before. Introduction of all genetic and ant colony optimization algorithm operators and settings are given here. Then follows the introduction to software witch was made to solve and visualize solutions of scheduling problem. A great number of plots and figures are used in the experimental chapter to explain what... [to full text]