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

Set Constraints and Logic Programming

AbstractSet constraints are inclusion relations between expressions denoting sets of ground terms over a ranked alphabet. They are the main ingredient in set-based program analysis. In this paper we describe a constraint logic programming languageclp(sc) over set constraints in the style of J. Jaffar and J.-L. Lassez (1987, “Proc. Symp. Principles of Programming Languages 1987,” pp. 111–119). The language subsumes ordinary logic programs over an Herbrand domain. We give an efficient unification algorithm and operational, declarative, and fixpoint semantics. We show how the language can be applied in set-based program analysis by deriving explicitly the monadic approximation of the collecting semantics of N. Heintze and J. Jaffar (1992, “Set Based Program Analysis”; 1990, “Proc. 17th Symp. Principles of Programming Languages,” pp. 197–209)

A CHR-based Implementation of Known Arc-Consistency

In classical CLP(FD) systems, domains of variables are completely known at the beginning of the constraint propagation process. However, in systems interacting with an external environment, acquiring the whole domains of variables before the beginning of constraint propagation may cause waste of computation time, or even obsolescence of the acquired data at the time of use. For such cases, the Interactive Constraint Satisfaction Problem (ICSP) model has been proposed as an extension of the CSP model, to make it possible to start constraint propagation even when domains are not fully known, performing acquisition of domain elements only when necessary, and without the need for restarting the propagation after every acquisition. In this paper, we show how a solver for the two sorted CLP language, defined in previous work, to express ICSPs, has been implemented in the Constraint Handling Rules (CHR) language, a declarative language particularly suitable for high level implementation of constraint solvers.Comment: 22 pages, 2 figures, 1 table To appear in Theory and Practice of Logic Programming (TPLP

Experiments in reactive constraint logic programming1This paper is the complete version of a previous paper published in [14].1

AbstractIn this paper we study a reactive extension of constraint logic programming (CLP). Our primary concerns are search problems in a dynamic environment, where interactions with the user (e.g. in interactive multi-criteria optimization problems) or interactions with the physical world (e.g. in time evolving problems) can be modeled and solved efficiently. Our approach is based on a complete set of query manipulation commands for both the addition and the deletion of constraints and atoms in the query. We define a fully incremental model of execution which, contrary to other proposals, retains as much information as possible from the last derivation preceding a query manipulation command. The completeness of the execution model is proved in a simple framework of transformations for CSLD derivations, and of constraint propagation seen as chaotic iteration of closure operators. A prototype implementation of this execution model is described and evaluated on two applications

LOGIC AND CONSTRAINT PROGRAMMING FOR COMPUTATIONAL SUSTAINABILITY

Computational Sustainability is an interdisciplinary field that aims to develop computational and mathematical models and methods for decision making concerning the management and allocation of resources in order to help solve environmental problems. This thesis deals with a broad spectrum of such problems (energy efficiency, water management, limiting greenhouse gas emissions and fuel consumption) giving a contribution towards their solution by means of Logic Programming (LP) and Constraint Programming (CP), declarative paradigms from Artificial Intelligence of proven solidity. The problems described in this thesis were proposed by experts of the respective domains and tested on the real data instances they provided. The results are encouraging and show the aptness of the chosen methodologies and approaches. The overall aim of this work is twofold: both to address real world problems in order to achieve practical results and to get, from the application of LP and CP technologies to complex scenarios, feedback and directions useful for their improvement

An algorithm for linear constraint solving: its incorporation in a prolog meta-interpreter for CLP

AbstractThe paper presents an incremental and efficient algorithm for testing the satisfiability of systems of linear equalities, inequalities (strict or unrestricted), and disequalities. In addition, it describes the incorporation of that algorithm into a metalevel interpreter capable of processing both tree constraints and the mentioned linear constraints in the domain of rationals. Important characteristics of the described algorithm are (1) detection of fixed variables within the context of Gaussian elimination, including the simplex method. (2) efficient dereferencing by considering subclasses of solved forms, and (3) efficient testing of inconsistencies between equality and disequality subclasses. The metalevel interpreter is written in Prolog. Examples of its usage are provided. Finally, the paper outlines how the approach may be generalized to consider the efficient and incremental testing of constraint satisfiability in various domains