Optimal Placement of Valves in a Water Distribution Network with CLP(FD)

This paper presents a new application of logic programming to a real-life problem in hydraulic engineering. The work is developed as a collaboration of computer scientists and hydraulic engineers, and applies Constraint Logic Programming to solve a hard combinatorial problem. This application deals with one aspect of the design of a water distribution network, i.e., the valve isolation system design. We take the formulation of the problem by Giustolisi and Savic (2008) and show how, thanks to constraint propagation, we can get better solutions than the best solution known in the literature for the Apulian distribution network. We believe that the area of the so-called hydroinformatics can benefit from the techniques developed in Constraint Logic Programming and possibly from other areas of logic programming, such as Answer Set Programming.Comment: Best paper award at the 27th International Conference on Logic Programming - ICLP 2011; Theory and Practice of Logic Programming, (ICLP'11) Special Issue, volume 11, issue 4-5, 201

Translation-based Constraint Answer Set Solving

We solve constraint satisfaction problems through translation to answer set programming (ASP). Our reformulations have the property that unit-propagation in the ASP solver achieves well defined local consistency properties like arc, bound and range consistency. Experiments demonstrate the computational value of this approach.Comment: Self-archived version for IJCAI'11 Best Paper Track submissio

Symmetry Breaking for Answer Set Programming

In the context of answer set programming, this work investigates symmetry detection and symmetry breaking to eliminate symmetric parts of the search space and, thereby, simplify the solution process. We contribute a reduction of symmetry detection to a graph automorphism problem which allows to extract symmetries of a logic program from the symmetries of the constructed coloured graph. We also propose an encoding of symmetry-breaking constraints in terms of permutation cycles and use only generators in this process which implicitly represent symmetries and always with exponential compression. These ideas are formulated as preprocessing and implemented in a completely automated flow that first detects symmetries from a given answer set program, adds symmetry-breaking constraints, and can be applied to any existing answer set solver. We demonstrate computational impact on benchmarks versus direct application of the solver. Furthermore, we explore symmetry breaking for answer set programming in two domains: first, constraint answer set programming as a novel approach to represent and solve constraint satisfaction problems, and second, distributed nonmonotonic multi-context systems. In particular, we formulate a translation-based approach to constraint answer set solving which allows for the application of our symmetry detection and symmetry breaking methods. To compare their performance with a-priori symmetry breaking techniques, we also contribute a decomposition of the global value precedence constraint that enforces domain consistency on the original constraint via the unit-propagation of an answer set solver. We evaluate both options in an empirical analysis. In the context of distributed nonmonotonic multi-context system, we develop an algorithm for distributed symmetry detection and also carry over symmetry-breaking constraints for distributed answer set programming.Comment: Diploma thesis. Vienna University of Technology, August 201

Solving Real-Life Hydroinformatics Problems with Operations Research and Artificial Intelligence

Many real life problems in the hydraulic engineering literature can be modelled as constrained optimisation problems. Often, they are addressed in the literature through genetic algorithms, although other techniques have been proposed. In this thesis, we address two of these real life problems through a variety of techniques taken from the Artificial Intelligence and Operations Research areas, such as mixed-integer linear programming, logic programming, genetic algorithms and path relinking, together with hybridization amongst these technologies and with hydraulic simulators. For the first time, an Answer Set Programming formulation of hydroinformatics problems is proposed. The two real life problems addressed hereby are the optimisation of the response in case of contamination events, and the optimisation of the positioning of the isolation valves. The constraints of the former describe the feasible region of the Multiple Travelling Salesman Problem, while the objective function is computed by a hydraulic simulator. A simulation–optimisation approach based on Genetic Algorithms, mathematical programming, and Path Relinking, and a thorough experimental analysis are discussed hereby. The constraints of the latter problem describe a graph partitioning enriched with a maximum flow, and it is a new variant of the common graph partitioning. A new mathematical model plus a new formalization in logic programming are discussed in this work. In particular, the technologies adopted are mixed-integer linear programming and Answer Set Programming. Addressing these two real applications in hydraulic engineering as constrained optimisation problems has allowed for i) computing applicable solutions to the real case, ii) computing better solutions than the ones proposed in the hydraulic literature, iii) exploiting graph theory for modellization and solving purposes, iv) solving the problems by well suited technologies in Operations Research and Artificial Intelligence, and v) designing new integrated and hybrid architectures for a more effective solving