CAREER:Synthesis of Search Procedures for Constraint Programs

University Of Connecticut, Storrs CT

Investigators

Abstract

Proposal 0642906 "CAREER: Synthesis of Search Procedures for Constraint Programs" PI: Laurent D. Michel University of Connecticut Abstract This research aims at synthesizing constraint programs (CP) from high-level constraint programming models. Constraint programming is a method for solving complex optimization applications, which are ubiquitous in our society, are critical to many industries, and affect almost every aspect of our daily lives. However, current constraint programming methodologies require significant expertise to design and program search procedures, and consequently, are not yet widely used by optimization modelers. This is in contrast with modeling languages for mathematical programming, which are now highly automated. This project investigates the automatic synthesis of constraint programs from high-level models. Its approach exploits the ability of constraint programs to express combinatorial structures in individual constraints to derive key properties like symmetries or dominance for entire models. From these properties, it can reformulate and synthesize search procedures adapted to the underlying solver technology, such as constraint programming, local search, integer programming, or even hybrids. To educate the next generation of engineers, the PI is developing material targeting high school math and science teachers and will disseminate these efforts via the DaVinci initiative at the University of Connecticut. The Broader Impacts of this project include the development of a new generation of modeling languages and systems based on recent advances in programming languages, compilers and artificial intelligence; these will be able to serve a wider audience of optimization modelers.