A Modified Event Grouping Based Algorithm for The University Course Timetabling Problem

This paper presents a study of a modified event grouping based algorithm (MEGB) for university course timetabling problem (UCTP). Multiple models to describe the problem and multiple approaches to solving it are pointed out. The main idea of the modification is that through reduction on the generated solutions the execution time of the standard event grouping based algorithm (EGB) will be reduced, too. Also, an implementation of the modified algorithm based on the described approach is presented. The methodology, conditions and the aims of the experiment are described. The experimental results are analyzed and conclusions are made. When increasing the number of the groups, the execution time of the MEGB algorithm increases and equates with the execution time of the EGB algorithm. The best results are obtained with the first 30% of the groups formed. In these groupings, the execution time of the MEGB algorithm is much less than the execution time of the EGB algorithm. This is because, in the EGB algorithm, every change in the event ordinance creates a new timetable, and all events are repositioned on it. This process is optimized by creating a partial timetable, whereby the ordinance of events in groups before the current does not change. In addition, a comparative analysis between the MEGB algorithm and two other algorithms for UCTP, respectively a genetic algorithm with the local search method (GALS) and a local search algorithm based on chromatic classes (CCLS) is made as well. The obtained results show that the MEGB algorithm and the CCLS algorithm generate better solutions for smaller input data sets, while the GALS algorithm generates better solutions for larger input data sets. However, in terms of the execution time, it was ascertained that the GALS algorithm runs slowest among the others

Design and Analysis of a Relational Database for Behavioral Experiments Data Processing

In this paper, the results of a comparative analysis between different approaches to experimental data storage and processing are presented. Several studies related to the problem and some methods for solving it have been discussed. Different types of databases, ways of using them and the areas of their application are analyzed. For the purposes of the study, a relational database for storing and analyzing a specific data from behavioral experiments was designed. The methodology and conditions for conducting the experiments are described. Three different indicators were analyzed, respectively: memory required to store the data, time to load the data from an external file into computer memory and iteration time across all records through one cycle. The obtained results show that for storing a large number of records (in the order of tens of millions of rows), either dynamic arrays (stored on external media in binary file format), or an approach based on a local or remote database management system can be used. Regarding the data loading time, the fastest approach was the one that uses dynamic arrays. It outperforms significantly the approaches based on a local or remote database. The obtained results show that the dynamic arrays and the local data sets approaches iterated much faster across all data records than the remote database approach. The paper concludes with proposal for further developments towards using of web services

An Analysis of a Web Service based Approach for Experimental Data Sharing

This paper presents the results obtained from a comparative analysis of two methods for experimental data sharing. Several works related to the topic and some approaches for processing data have been discussed. Different technolgoies related to the web services, ways of using them and the areas of their application are analyzed. For the purposes of the study, a web service for retrieving specific data from a behavioral experiments database was developed.The methodology and conditions for conducting the experiments are described. Two different indicators are analyzed, respectively: time to retrieve the data from a database and iteration time across all records through one loop. The results show that when retrieving thousands of records both web service based approach and an approach based on a remote database server can be used. However, when retrieving millions of records, the fastest approach was the one that uses remote database server. The obtainedresultsshow that the dynamic arrays (containing strings) iterated much faster across all data records than the dataset approach

An Analysis of a Web Service based Approach for Experimental Data Sharing

This paper presents the results obtained from a comparative analysis of two methods for experimental data sharing. Several works related to the topic and some approaches for processing data have been discussed. Different technolgoies related to the web services, ways of using them and the areas of their application are analyzed. For the purposes of the study, a web service for retrieving specific data from a behavioral experiments database was developed.The methodology and conditions for conducting the experiments are described. Two different indicators are analyzed, respectively: time to retrieve the data from a database and iteration time across all records through one loop. The results show that when retrieving thousands of records both web service based approach and an approach based on a remote database server can be used. However, when retrieving millions of records, the fastest approach was the one that uses remote database server. The obtainedresultsshow that the dynamic arrays (containing strings) iterated much faster across all data records than the dataset approach.</span

Design and Analysis of a Relational Database for Behavioral Experiments Data Processing

In this paper, the results of a comparative analysis between different approaches to experimental data storage and processing are presented. Several studies related to the problem and some methods for solving it have been discussed. Different types of databases, ways of using them and the areas of their application are analyzed. For the purposes of the study, a relational database for storing and analyzing a specific data from behavioral experiments was designed. The methodology and conditions for conducting the experiments are described. Three different indicators were analyzed, respectively: memory required to store the data, time to load the data from an external file into computer memory and iteration time across all records through one cycle. The obtained results show that for storing a large number of records (in the order of tens of millions of rows), either dynamic arrays (stored on external media in binary file format), or an approach based on a local or remote database management system can be used. Regarding the data loading time, the fastest approach was the one that uses dynamic arrays. It outperforms significantly the approaches based on a local or remote database. The obtained results show that the dynamic arrays and the local data sets approaches iterated much faster across all data records than the remote database approach. The paper concludes with proposal for further developments towards using of web services