Work

Scimitar: Functional Programs as Optimization Problems

Year: 2024

Type: conference-paper

Abstract: Mixed integer linear programming is a powerful and widely used approach to solving optimization problems, but its expressiveness is limited. In this paper we introduce the optimization-aided language Scimitar, which encodes optimization problems using an expressive functional language, with a compiler that targets a mixed integer linear program solver. Scimitar provides easy access to encoding techniques that normally require expert knowledge, enabling solve-time conditional constraints, inlining, loop unrolling, and many other high-level language constructs. We give operational semantics for Scimitar and constraint encodings of various features. To demonstrate Scimitar, we present a number of examples and benchmarks including classic optimization domains and more complex problems. Our results indicate that Scimitar's use of a dedicated MILP solver is effective for expressively modeling optimization problems embedded within functional programs.

Source: ACM SIGPLAN International Symposium on New Ideas, New Paradigms, and Reflections on Programming and Software (Onward!)

DOI: 10.1145/3689492.3690051

Authors: Nate F. F. Bragg, Jeffrey S. Foster, Philip Zucker

Institutions: Tufts University, Draper Laboratory

Language: English

Topic: Logic, programming, and type systems

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W4403493467

FWCI:

Cites: 20

Cited by:

Related to: 10