In this paper we present novel algorithmic solutions for several resource
processing and data transfer multicriteria optimization problems. The results
of most of the presented techniques are strategies which solve the considered
problems (almost) optimally. Thus, the developed algorithms construct
intelligent strategies which can be implemented by agents in specific
situations. All the described solutions make use of the properties of the
considered problems and, thus, they are not applicable to a very general class
of problems.
The domains of data mining and knowledge discovery make use of large amounts
of textual data, which need to be handled efficiently. Specific problems, like
finding the maximum weight ordered common subset of a set of ordered sets or
searching for specific patterns within texts, occur frequently in this context.
In this paper we present several novel and practical algorithmic techniques for
processing textual data (strings) in order to efficiently solve multiple
problems.
The problem of efficiently delivering data within networks is very important
nowadays, especially in the context of the large volumes of data which are
being produced each year and of the increased data access needs of the users.
Efficient data delivery strategies must satisfy several types of Quality of
Service (QoS) constraints which are imposed by the data consumers. One
possibility of achieving this goal (particularly in the case of in-order data
transfers) is to choose a satisfactory network delivery path.