The dawn of the new century casts light on three dramatic economic challenges that will impact our future heavily: demography, globalization, and shortage of natural resources. Today we need to develop the technology that will allow our children to maintain our standard of living while using less energy and raw materials, putting less strain onto our ecosystem, competing on the global market, and having to support more retirees than ever before in history.

Therefore, we need to find ways to increase our economical efficiency. Computer science can play a decisive role when facing this challenge. Ever since the first algorithms were developed, computer scientists have studied methods how to minimize travel distances, resource consumptions, and work loads when providing a needed service. After more than 60 years of research, algorithmic computer science can offer a lot to help saving. However, the main impact of optimization is currently limited to large companies in few core application areas such as the transportation or the steel industry. Specialized algorithmic solutions have shown to be extremely successful in these domains where they yield multi-billion dollar savings every year. While the algorithmic technologies that were developed are by no means specific to the current areas of application, the main obstacle for a broader realization of their vast potential is largely due to the lacking ease of use. Therefore, we propose the Cornflower Project which we develop techniques that allow inexperienced users to exploit optimization power efficiently.

Optimization techniques have been developed in three historically separate research areas: constraint programming, operations research, and algorithm theory. While the main focus of the project is to provide a high level of automization and algorithms that can be hooked to intuitive modeling primitives that facilitate the use of intelligent optimization support, we do not stop at the boundaries of traditional research areas. Instead, we integrate and hybridize ideas developed in different communities in order to provide easily accessible high performance optimization technology. Particularly, we focus on the development of high-level constraints that allow users to model the problems as conjunctions of intuitive substructures and provide hybrid methods for their efficient combination. Moreover, we develop automization techniques for the handling of symmetries that can the cause of severe inefficiencies when handled poorly.

The provision of accessible intelligent optimization support is one of the main objectives of computational research. The main goal of the Cornflower project is to solve the algorithmic problems that arise in the context of optimization driven decision support systems that are intuitive to use and that provide a high level of automization. By making algorithms and methods publicly available in the Cornflower Library, the project contributes to widening the access to computation decision support, an effort that, if it succeeds, can be expected to have a major impact on economy and the society as a whole.

Broadening the accessibility of computational decision support while breaking the barriers between theoretical and practical computer science goes hand in hand with the educational goals of the project. Optimization techniques play an ever more important role for many other CS disciplines like machine learning, databases, and approximation algorithms. At the same time, they require both sound theoretical knowledge and practical implementation skills. By developing optimization courses that ground theory in practice, Cornflower helps to educate the next generation of experts in combinatorial algorithms both on the undergraduate and the graduate level, while students moving on to other disciplins take away a sound understanding how to tackle combinatorial problems and how to utilize standard solvers for their own purposes.

Attracting both students who are mainly interested in technical methodology as well as those who are primarily attracted to specific applications is also a promising approach to broadening participation in science at large. In 2006, the PI accompanies the Artemis project at Brown University for which will take over the responsibility completely starting in 2007. Artemis is an outreach program to encourage high-school girls to pursue careers in science and engineering. The primary focus of Artemis is a five-week summer program in which the Artemis students learn about various practical and conceptual aspects of computer science, are introduced to women scientists and role models, and participate in educational and confidence-building activities that convey the excitement of working scientifically towards a greater end.