Online Computer Science Degree Guide: Constraint Programming

Constraint programming is a powerful but often overlooked programming language sometimes used by massive companies such as Siemens, Lufthansa, and Renault. Controlling highly complex management systems for petroleum refineries or simply managing staff schedules, the economic and industrial implications of this branch of computer science are great. The Guide to Constraint Programming Resources points to highly valuable materials which explain this study as well as its practical applications. As with the many guides in our computer science collection, beginning students of computer science or more advanced users looking to diversify their skill sets can benefit from this resource.

Overview

The science of constraint programming (CP) deals with the relations of variables in computational systems. It is the function of CP to describe problems related to constraints and also to solve them. Constraints are relations of values which limit possible outcomes. Early forms of CP were highly influenced by logic, making constraints into logic problems. Currently, constraints are often found with functional programming and other types of programming paradigms.

In computer science, this area deals highly with artificial intelligence and search functions. One of constraint programming’s major goals is to find constraints which most effectively optimize function. Challenges that deal with this is are called Constraint Satisfaction Problems (CSP). Planning and scheduling are among the most popular uses of CP, as can be seen in areas such as Supply Chain Management. In real-world applications, CSP systems are mainly used for scheduling and configuration, though they can be used in linguistics or for graphical systems.

This study of unknowns can be helpful for problems related to resource allocation and scheduling. While many aspects of constraint programming deal with electronically centered uses, there are many applications beyond pure computer science. The practical applications of this study can be found in many areas and include the manufacture of food products, establishing beneficial financial practices and the refining of materials such as petroleum. CP makes it possible to develop highly complex systems which regulate materials, having a dramatic impact on industry and the economy. Not limited strictly to the study of computers, CP can be used effectively in many industrial and business environments.

Constraint Programming FAQs

Significant questions regarding constraint programming are addressed here through a number of focused resources. Information about constraint detection, solutions, and constraint satisfaction problems provide an understanding of many areas related to constraint programming. Further, current development and the future of the discipline are expounded upon. Qualities that are necessary for the success of the discipline and current trends in the field are among topics examined. You will also find links to some tools which are helpful for the development of applications as well as prominent software libraries.

• Constraint Solving FAQ answers fundamental as well as more advanced questions regarding CP with an emphasis on solving issues related to constraints. Technical details such as hard and soft constraints are explained in addition to practical concerns such as choosing a solver or real-life applications.
• What is Constraint Programming? –  Learn how to use Prolog syntax as a host language and discover what its benefits are.  Further, examples showing how to deal with crypto-arithmetic puzzles using constraint programming are provided.
• How Do You Program with Prolog? – A logic programming language and major component of CP, Prolog is detailed through explanations and examples of code. Further, a section where you can test your own code is provided so that you can become more familiar with its practical use.
• What is Mutlithreaded Constraint Programming? – Multithreaded parallelization can be used in order to make constraint programming more effective in search performance. A mixed approach which utilizes qualities of CP and multithreading allows for best-first results in addition to the standard approach.
• How Can Constraint Programming be Applied Graphically? – An example of a graphical window management system shows how graphical applications can be more effective for some causes. Badros, Nichols, and Borning display how constraint programming can make a highly intelligent window manager.
• How Do Classes and Prototypes Differ in Object Oriented Languages? – Problems surrounding classes and metaclasses result in confusion and unnecessary complication. Prototypes may be a successful alternative.
• What are Constraint Satisfaction Problems? – Constraint based reasoning has been greatly advanced through the exploration of constraint satisfaction problems. These problems consist of sets of variables, finite domains, and set of constraints.
• What is Backtracking or Constraint Propagation? – Constraints can drastically reduce search space through forward checking and propagation. Additionally, propagation results in more consistent searches that can be carried out more quickly.
• What Approaches are Used in Constraint Satisfaction Problems? – Common approaches to issues posed by the wide variety of constraint-satisfaction problems are surveyed in Vipin Kumar’s article. Constraint propagation and backtracking as well as hybrid approaches are all explained.
• What are Over-Constrained Problems? – In many cases, especially in real-world applications, a solution may not exist. These are known as over-constrained systems. In order to find a solution the problem must be weakened.
• How are Search Related Aspects of CP Advancing? – More active search procedures may be the future of constraint-programming solvers. Instead of impact based searches, those that are activity based will improve search performance.
• How is Constraint Programming used for Data Mining and Machine Learning? – Constraints can be very useful for solving learning problems or for data mining. Typically, tools created are made with specific functions in mind, not allowing for general use. If programs were made to be more general and flexible, they could have higher functionality and make greater contributions to data mining.
• How is Constraint Programming Developing on a Large Scale? – The current and future state of constraint programming are examined by a number of authors in this collection of texts which considers the development of related tools, practical implementation and graph friendly models. Significant issues surrounding the topic such as redundancy and the need for highly accurate technical systems in safety critical settings make this text especially relevant.
• How is Constraint Programming related to Graphical Modeling? is an in-depth lecture which explores the uses of CP and graphical models through the example of AND/OR searches. Utilizing a number of diagrams and clear explanations, this presentation illustrates significant structures used in the discipline.
• Is the Future for Constraint Programming Good or Bad? – Modeling is necessary to the success of constraint programming, despite the emphasis placed on operations research and solution methods. The future of constraint programming relies upon uses of modeling; depending on how modeling is utilized, the future may be good or bad.
• What Tools Can I Use for Solving Constraint Satisfaction Problems? – CHOCO is a java library that can be used for solving constraint satisfaction problems as well as constraint programming in general. Applicable for the creation of many useable programs, CHOCO is a valuable tool.
• What Tools Can I Use for Developing Constraint Programming Related Applications?- ECLiPSe is used in developing constraint programming applications. It is a widely used and flexible open –source language which is compatible with Prolog.

Additional Resources

Tools for further exploring and better understanding the study of constraint programming are provided in this section. Interactive tutorials which challenge users to provide accurate code while explaining how to work most effectively are among the resources. Also available in this section are additional software libraries which are helpful for creating applications or for solving constraint satisfaction problems. Other resources include prominent related journals and associations.

• Google CP Solver – Using Python and C++ libraries, Google’s constraint programming solver works on 32 bit and 64 bit architectures. Provided documentation explains how to best use the program as well as how to build dependencies for different systems.
• Gecode/R is a Ruby interface version of the Gecode open source library which can be used in constraint programming. This interface is highly user friendly and is a good starting place, or tool for those with little previous experience.
• Association for Constraint Programming – The ACP works to promote this study in the scientific world and encourage its development on multiple levels. Beyond this goal, the ACP is dedicated to improving the academic understanding of the study and seeing its use in the industrial world.
• The Constraint Applications Blog is run by Helmut Simonis, who is a researcher at the Cork Constraint Computation Center, and the applications editor of Constraints. Here you can find up to date news about constraint programming and its practical applications through first-hand explanations of programs developed for industry.
• Constraints Tutorials – A series of online resources provide lectures, slides, and diagrams explaining the fundamentals of constraint programming. Tutorials for beginners which cover major areas such as constraint satisfaction and over-constraint are provided here.
• Constraints is a peer-reviewed scientific journal dedicated to the study of constraint programming. Approaching the study with a multi-disciplinary focus, this journal is a point of convergence for those interested in understanding constraint in the context of programming.
• Integrating Energy Engineering & Performance Modeling Into The Design Process is a guide which is intended to enhance energy engineering and efficiency. Performance modeling is one of the methods available to architects and engineers for improving the performance of their projects.
• Journal of Artificial Intelligence Research – While it includes research on all areas of artificial intelligence, JAIR provides many articles which explore constraints and CSP. Available entirely online, it is possible to read full-text versions of articles found in over forty one volumes.
• Gecode/R is a Ruby interface version of the Gecode open source library which can be used in constraint programming. This interface is highly user friendly and is a good starting place, or tool for those with little previous experience.