Combining Relational Algebra, SQL, Constraint Modelling, and Local Search

The goal of this paper is to provide a strong integration between constraint modelling and relational DBMSs. To this end we propose extensions of standard query languages such as relational algebra and SQL, by adding constraint modelling capabilities to them. In particular, we propose non-deterministic extensions of both languages, which are specially suited for combinatorial problems. Non-determinism is introduced by means of a guessing operator, which declares a set of relations to have an arbitrary extension. This new operator results in languages with higher expressive power, able to express all problems in the complexity class NP. Some syntactical restrictions which make data complexity polynomial are shown. The effectiveness of both extensions is demonstrated by means of several examples. The current implementation, written in Java using local search techniques, is described. To appear in Theory and Practice of Logic Programming (TPLP)Comment: 30 pages, 5 figure

Uma abordagem orientada por objectos para meta-heurísticas multiobjectivo

Nesta dissertação convergem algumas linhas de investigação na área das meta-heurísticas que, recentemente, têm vindo a ser objecto de particular atenção: a flexibilização, ou seja, a introdução de mecanismos de modificação de componentes e estratégias elementares, o desenvolvimento de abordagens orientadas por objectos, e a adaptação a contextos multiobjectivo. Esta convergência justifica-se pelo facto de as abordagens orientadas por objectos promoverem naturalmente a flexibilização, e pela constatação da inexistência, até ao momento, de abordagens orientadas por objectos para a área das metaheurísticas multiobjectivo. Foi feita uma análise e sistematização do domínio e, em particular, das metaheurísticas multiobjectivo, com ênfase na perspectiva da flexibilização. Esta sistematização fundamenta a proposta de um template para pesquisa local multiobjectivo, e de um conjunto de estratégias genéricas de flexibilização

Local++: A C++ Framework for Local Search Algorithms

Local search is an emerging paradigm for combinatorial search which has been recently shown to be very effective for a large number of combinatorial problems. It is based on the idea of navigating the search space by iteratively stepping from one solution to one of its neighbors, which are obtained by applying a simple local change to it. In this paper we present Local++, an object-oriented framework to be used as a general tool for the development and the implementation of local search algorithms in C++. The framework comprises a hierarchy of abstract template classes, one for each local search technique taken into account (i.e., hill-climbing, simulated annealing, and tabu search). Each class specifies and implements the invariant part of the algorithm built according to the technique, and is supposed to be specialized by a concrete class once a given search problem is considered, so as to implement the problem-dependent part of the algorithm. Local++ comprises also a se..