IJCAI 2021poster4 citations
Automatic Design of Heuristic Algorithms for Binary Optimization Problems
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.
Heuristic Search and Game Playing: Combinatorial Search and OptimisationHeuristic Search and Game Playing: Meta-Reasoning and Meta-HeuristicsHeuristic Search and Game Playing: Heuristic SearchMultidisciplinary Topics and Applications: Autonomic Computing
BibTeX
@inproceedings{ijcai2021p672,
title = {Automatic Design of Heuristic Algorithms for Binary Optimization Problems},
author = {de Souza, Marcelo},
booktitle = {Proceedings of the Thirtieth International Joint Conference on
Artificial Intelligence, {IJCAI-21}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
editor = {Zhi-Hua Zhou},
pages = {4881--4882},
year = {2021},
month = {8},
note = {Doctoral Consortium},
doi = {10.24963/ijcai.2021/672},
url = {https://doi.org/10.24963/ijcai.2021/672},
}