---
title: "Automatic Design of Heuristic Algorithms for Binary Optimization Problems"
authors:
  - "Marcelo de Souza"
doi: "10.24963/ijcai.2021/672"
url: "https://ijcai.org/proceedings/2021/672"
pdf: "https://ijcai.org/proceedings/2021/0672.pdf"
venue: "Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence"
year: 2021
pages: "4881-4882"
track: "Doctoral Consortium"
keywords:
  - "Heuristic Search and Game Playing: Combinatorial Search and Optimisation"
  - "Heuristic Search and Game Playing: Heuristic Search"
  - "Heuristic Search and Game Playing: Meta-Reasoning and Meta-Heuristics"
  - "Multidisciplinary Topics and Applications: Autonomic Computing"
---

# Automatic Design of Heuristic Algorithms for Binary Optimization Problems

Marcelo de Souza

*Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence*, pages 4881-4882. DOI: [10.24963/ijcai.2021/672](https://doi.org/10.24963/ijcai.2021/672)

## Abstract

In this work we present AutoBQP, a heuristic solver for binary optimization problems. It applies automatic algorithm design techniques to search for the best heuristics for a given optimization problem. Experiments show that the solver can find algorithms which perform better than or comparable to state-of-the-art methods, and can even find new best solutions for some instances of standard benchmark sets.