Essentials Of Constraint Programming

The use of constraints had its scientific and commercial breakthrough in the 1990s. Programming with constraints makes it possible to model and specify problems with uncertain, incomplete information and to solve combi natorial problems, as they are abundant in industry and commerce, such as scheduling, planning, transportation, resource allocation, layout, design, and analysis. This book is a short, concise, and complete presentation of constraint programming and reasoning, covering theoretical foundations, algorithms, implementations, examples, and applications. It is based on more than a decade of experience in teaching and research about this subject. This book is intended primarily for graduate students, researchers, and practitioners in diverse areas of computer science and related fields, including programming languages, computational logic, symbolic computation, and ar tificial intelligence. The book is complemented by a web-page with teaching material, software, links, and more. We take the reader on a step-by-step journey through the world of constraint-based programming and constraint reasoning. Feel free to join in ... Acknowledgements Thorn thanks his wife Andrea and his daughter Anna - for everything. He dedicates his contribution to the book to the memory of his mother, Grete. Slim thanks his wife N abila and his daughters Shirine and Amira for their ongoing support and patience.

Constraint programming is a powerful paradigm for solving combinatorial search problems that draws on a wide range of techniques from artificial intelligence, computer science, databases, programming languages, and operations research. Constraint programming is currently applied with success to many domains, such as scheduling, planning, vehicle routing, configuration, networks, and bioinformatics.The aim of this handbook is to capture the full breadth and depth of the constraint programming field and to be encyclopedic in its scope and coverage. While there are several excellent books on constraint programming, such books necessarily focus on the main notions and techniques and cannot cover also extensions, applications, and languages. The handbook gives a reasonably complete coverage of all these lines of work, based on constraint programming, so that a reader can have a rather precise idea of the whole field and its potential. Of course each line of work is dealt with in a survey-like style, where some details may be neglected in favor of coverage. However, the extensive bibliography of each chapter will help the interested readers to find suitable sources for the missing details. Each chapter of the handbook is intended to be a self-contained survey of a topic, and is written by one or more authors who are leading researchers in the area.The intended audience of the handbook is researchers, graduate students, higher-year undergraduates and practitioners who wish to learn about the state-of-the-art in constraint programming. No prior knowledge about the field is necessary to be able to read the chapters and gather useful knowledge. Researchers from other fields should find in this handbook an effective way to learn about constraint programming and to possibly use some of the constraint programming concepts and techniques in their work, thus providing a means for a fruitful cross-fertilization among different research areas.The handbook is organized in two parts. The first part covers the basic foundations of constraint programming, including the history, the notion of constraint propagation, basic search methods, global constraints, tractability and computational complexity, and important issues in modeling a problem as a constraint problem. The second part covers constraint languages and solver, several useful extensions to the basic framework (such as interval constraints, structured domains, and distributed CSPs), and successful application areas for constraint programming. - Covers the whole field of constraint programming- Survey-style chapters- Five chapters on applications

Constraints are everywhere: most computational problems can be described in terms of restrictions imposed on the set of possible solutions, and constraint programming is a problem-solving technique that works by incorporating those restrictions in a programming environment. It draws on methods from combinatorial optimisation and artificial intelligence, and has been successfully applied in a number of fields from scheduling, computational biology, finance, electrical engineering and operations research through to numerical analysis. This textbook for upper-division students provides a thorough and structured account of the main aspects of constraint programming. The author provides many worked examples that illustrate the usefulness and versatility of this approach to programming, as well as many exercises throughout the book that illustrate techniques, test skills and extend the text. Pointers to current research, extensive historical and bibliographic notes, and a comprehensive list of references will also be valuable to professionals in computer science and artificial intelligence.

Constraints; Simplification, optimization and implication; Finite constraint domains; Constraint logic programming; Simple modeling; Using data structures; Controlling search; Modelling with finite domain constraints; Advanced programming techniques; CLP systems; Other constraint programming languages; Constraint databases; Index.

Constraint programming aims at supporting a wide range of complex applications, which are often modeled naturally in terms of constraints. Early work, in the 1960s and 1970s, made use of constraints in computer graphics, user interfaces, and artificial intelligence. Such work introduced a declarative component in otherwise-procedural systems to reduce the development effort.

Upper-division textbook covering foundations of constraint programming and applications to scheduling, optimisation etc.

Programming languages are often classified according to their paradigms, e.g. imperative, functional, logic, constraint-based, object-oriented, or aspect-oriented. A paradigm characterizes the style, concepts, and methods of the language for describing situations and processes and for solving problems, and each paradigm serves best for programming in particular application areas. Real-world problems, however, are often best implemented by a combination of concepts from different paradigms, because they comprise aspects from several realms, and this combination is more comfortably realized using multiparadigm programming languages. This book deals with the theory and practice of multiparadigm constraint programming languages. The author first elaborates on programming paradigms and languages, constraints, and the merging of programming concepts which yields multiparadigm (constraint) programming languages. In the second part the author inspects two concrete approaches on multiparadigm constraint programming – the concurrent constraint functional language CCFL, which combines the functional and the constraint-based paradigms and allows the description of concurrent processes; and a general framework for multiparadigm constraint programming and its implementation, Meta-S. The book is appropriate for researchers and graduate students in the areas of programming and artificial intelligence.

This book tackles classic problems from operations research and circuit design using a logic programming language embedding consistency techniques, a paradigm emerging from artificial intelligence research. Van Hentenryck proposes a new approach to solving discrete combinatorial problems using these techniques.Logic programming serves as a convenient language for stating combinatorial problems, but its "generate and test" paradigm leads to inefficient programs. Van Hentenryck's approach preserves one of the most useful features of logic programming - the duality of its semantics - yet allows a short development time for the programs while preserving most of the efficiency of special purpose programs written in a procedural language.Embedding consistency techniques in logic programming allows for ease and flexibility of programming and short development time because constraint propagation and tree-search programming are abstracted away from the user. It also enables logic programs to be executed efficiently as consistency techniques permit an active use of constraints to remove combinations of values that cannot appear in a solution Van Hentenryck presents a comprehensive overview of this new approach from its theoretical foundations to its design and implementation, including applications to real life combinatorial problems.The ideas introduced in "Constraint Satisfaction in Logic Programming "have been used successfully to solve more than a dozen practical problems in operations research and circuit design, including disjunctive scheduling, warehouse location, cutting stock car sequencing, and microcode labeling problems.Pascal Van Hentenryck is a member of the research staff at the European Computer Industry Research Centre. "Constraint Satisfaction in Logic Programming" is based on research for the Centre's CHIP project. As an outgrowth of this project, a new language (CHIP) that will include consistency techniques has been developed for commercial use. The book is included in the Logic Programming series edited by Ehud Shapiro.

The definitive reference on Constraint Handling Rules, from the creator of the language.

This book constitutes the proceedings of the First International Conference on Principles and Practice of Constraint Programming, CP '95, held in Cassis near Marseille, France in September 1995. The 33 refereed full papers included were selected out of 108 submissions and constitute the main part of the book; in addition there is a 60-page documentation of the four invited papers and a section presenting industrial reports. Thus besides having a very strong research component, the volume will be attractive for practitioners. The papers are organized in sections on efficient constraint handling, constraint logic programming, concurrent constraint programming, computational logic, applications, and operations research.