CLPGUI: a generic graphical user interface for constraint logic programming over finite domains

CLPGUI is a graphical user interface for visualizing and interacting with constraint logic programs over finite domains. In CLPGUI, the user can control the execution of a CLP program through several views of constraints, of finite domain variables and of the search tree. CLPGUI is intended to be used both for teaching purposes, and for debugging and improving complex programs of realworld scale. It is based on a client-server architecture for connecting the CLP process to a Java-based GUI process. Communication by message passing provides an open architecture which facilitates the reuse of graphical components and the porting to different constraint programming systems. Arbitrary constraints and goals can be posted incrementally from the GUI. We propose several dynamic 2D and 3D visualizations of the search tree and of the evolution of finite domain variables. We argue that the 3D representation of search trees proposed in this paper provides the most appropriate visualization of large search trees. We describe the current implementation of the annotations and of the interactive execution model in GNU-Prolog, and report some evaluation results.Comment: 16 pages; Alexandre Tessier, editor; WLPE 2002, http://xxx.lanl.gov/abs/cs.SE/020705

Mixed integer-linear formulations of cumulative scheduling constraints - A comparative study

This paper introduces two MILP models for the cumulative scheduling constraint and associated pre-processing filters. We compare standard solver performance for these models on three sets of problems and for two of them, where tasks have unitary resource consumption, we also compare them with two models based on a geometric placement constraint. In the experiments, the solver performance of one of the cumulative models, is clearly the best and is also shown to scale very well for a large scale industrial transportation scheduling problem

When do bounds and domain propagation lead to the same search space

This paper explores the question of when two propagation-based constraint systems have the same behaviour, in terms of search space. We categorise the behaviour of domain and bounds propagators for primitive constraints, and provide theorems that allow us to determine propagation behaviours for conjunctions of constraints. We then show how we can use this to analyse CLP(FD) programs to determine when we can safely replace domain propagators by more efficient bounds propagators without increasing search space

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

Constraint logic programming for fault-tolerant distributed systems

This paper presents key notions of Constraint Logic Programming (CLP), which is a young programming paradigm oriented toward solving difficult discrete highly combinatorial problems by making active use of constraints on the basis of mechanisms of Logic Programming. Being the subject of intensive research all over the world, CLP has already been used successfully in a large variety of application areas. As one of the important applications where CLP demonstrates its potential, we propose CLP-based procedures of solving the problems of optimal resource and task allocation at the stages of design and operation of Fault-Tolerant Distributed Technical Systems.Peer Reviewe

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

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

AUTOMATED SCHEDULE GENERATION AND ANALYSIS FROM A CONSTRUCTION REQUIREMENT PERSPECTIVE

Ph.DDOCTOR OF PHILOSOPH

Ritmos cognitivos y algoritmos evolutivos en la programación de horarios universitarios

The main purpose of this research is to design a methodology based on evolutionary algorithms to university timetable scheduling. This methodology will consider the students’ cognitive rhythms, which establish that teaching certain subjects in specific time intervals is much better than other techniques. This project takes place in three phases. First of all, there is a description of the different techniques used to solve this problem. Then, a new methodology based on cognitive rhythms and evolutionary algorithms is proposed, and finally, different methodologies are compared to determine the best. It is concluded that evolutionary algorithms are more efficient than other techniques in the university timetable scheduling. Future lines of research will determine the impact of these techniques within the students’ learning process.El propósito de esta investigación es diseñarr una metodología basada en algoritmos evolutivos para la programación de horarios universitarios. Esta metodología considerará los ritmos cognitivos de los estudiantes, los cuales establecen que enseñar algunas materias en intervalos de tiempo específicos es mejor que otras técnicas. Este proyecto es desarrollado en tres fases. Primero se realiza una descripción de las diferentes técnicas empleadas para solucionar este problema. Posteriormente una nueva metodología basada en ritmos cognitivos y algoritmos evolutivos es propuesta. Finalmente diferentes metodologías son comparadas para determinar la mejor. Se concluye que los algoritmos evolutivos son más eficientes que otras técnicas en la programación de horarios universitarios. Futuras líıneas de investigación determinarán el impacto de estas técnicas en los procesos de aprendizaje de los estudiantes

Cost and benefits design optimization model for fault tolerant flight control systems

Requirements and specifications for a method of optimizing the design of fault-tolerant flight control systems are provided. Algorithms that could be used for developing new and modifying existing computer programs are also provided, with recommendations for follow-on work