Automatic Design of Heuristic Algorithms for Binary Optimization Problems

被引：0
|
作者：
de Souza, Marcelo [1 ,2 ]
机构：
[1] Univ Fed Rio Grande do Sul, Porto Alegre, RS, Brazil
[2] Santa Catarina State Univ, Florianopolis, SC, Brazil
来源：
PROCEEDINGS OF THE THIRTIETH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, IJCAI 2021 | 2021年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
引用
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页码：4881 / 4882
页数：2
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