Six workshops have been accepted for CP'15.
During recent years, Biology has become a source of challenging problems for the entire field of Computer Science in general, and for the areas of computational logic and constraint programming in particular. The WCB workshop, the 11th of the series, aims at exchanging ideas between researchers and collecting, if possible, new problems to be faced in the next future by our community. Revised, extended versions of WCB papers are welcomed to a special track in the ALMOB Journal (IF 1.86).
Bin Packing and Placement problems are an old but still challenging topic that has been tackled with different approaches. On the one hand, the aim of this workshop is to share recent progress made on pure problems by using any algorithmic technique (or a mix) like Mixed Integer Linear Programming, Constraint Programming, Logic Programming, Local Search or Evolutionary Algorithms. On the other hand, the aim is to present challenging problems formulated and/or solved by these methods, or challenging extensions that have a practical interest and for which pure methods do not directly work.
Constraint Satisfaction Problems (CSP's) and Boolean Satisfiability Problems (SAT) have much in common. However, they also differ in many important aspects, which result in major differences in solution techniques. More importantly, the CSP and SAT communities, while to some extent interacting with each other, are mostly separate communities with separate conferences and meetings. This workshop is designed as a venue for bridging the gap and for cross-fertilization between the two communities, in terms of ideas, problems, techniques, and results.
Constraint Programming (CP) is a powerful set of techniques to model and solve combinatorial problems, which are ubiquitous in academia and industry. The last ten years or so have witnessed significant research devoted to modelling and solving problems with constraints. CP has been successfully used for tackling a wide range of real-life complex applications, however finding a good model of a given problem often requires considerable expertise and time. The key goals of this workshop are to extend the understanding of constraint modelling, and to automate aspects of modelling or model reformulation to extend the reach of constraint solvers on difficult problems and ease the task of modelling.
Teaching constraint programming (CP) is important: it allows us to increase the uptake of the technology and to train the next generation of researchers and practitioners. We are holding the first workshop on teaching constraint programming, whose aim is to help participants improve the quality of the teaching of constraint programming. It will give participants the opportunity to discuss the difficulties they encounter and the strategies they have employed to teach effectively. We aim to share best practice and teaching materials from both academia and industry.
Business Analytics and Big Data tools have recently emerged as a major (perhaps the main) driver for innovation in business and industry. Many firms are exploring the opportunities of these new technologies to gain a competitive advantage and many businesses are adding product features built on predictive insights. The goal of this workshop is to increase awareness within the CP community of the previous opportunity, and ideally present concrete future directions for research and applications. The workshop will feature invited talks by leading experts in this domain, as well as an interactive panel discussion.