@inproceedings{b498ad7843984a499940a20999ec4b5a,
title = "SAT-based big-step local search",
abstract = "This paper introduces a hybrid search method for optimization problems which combines techniques from Local Search methods and from SAT-based methods. At each iteration, the method performs a 'big-step' move on a subset of variables of the current solution. This step is achieved by encoding the big-step itself as an optimization problem and solving it using a SAT (MaxSAT) solver such that the solution of the big-step results in a higher-quality solution to the entire problem. Experimentation illustrates a clear benefit of the approach over both methods: Local Search methods and SAT-based methods.",
keywords = "Constraints, Examination timetabling, Local search, Maxsat, Optimization, Sat, Sat solver, Scheduling, Simulated annealing",
author = "Morad Muslimany and Michael Codish",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2018 ; Conference date: 20-09-2018 Through 23-09-2018",
year = "2018",
month = sep,
day = "1",
doi = "10.1109/SYNASC.2018.00029",
language = "English",
series = "Proceedings - 2018 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2018",
publisher = "Institute of Electrical and Electronics Engineers",
pages = "109--116",
booktitle = "Proceedings - 2018 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2018",
address = "United States",
}