{"type":"ScholarlyArticle","title":"Discrete Lagrangian-Based Search for Solving MAX-SAT Problems","authors":[{"name":"Benjamin W. Wah","slug":"benjamin-w-wah","given":"Benjamin W.","family":"Wah","affiliation":""},{"name":"Yi Shang","slug":"yi-shang","given":"Yi","family":"Shang","affiliation":""}],"abstract":"Weighted maximum satisfiability problems (MAX-SAT) are difficult to solve due to the large number of local minima in their search space. In this paper we propose a new discrete Lagrangian based search method (DLM) for solving these problems. Instead of restarting from a new point when the search reaches a local minimum, the Lagrange multipliers in DLM provide a force to lead the search out of the local minimum and move it in a direction provided by the multipliers. Since DLM has very few parameters to be tuned, it can be made deterministic and the results, reproducible. We compare DLM with GRASP in solving a large set of test problems, and show that it finds better so lutions and is substantially faster. DLM has a solid theoretical foundation that can be used as a systematic approach for solving general discrete optimization problems.","doi":null,"url":"https://ijcai.org/proceedings/1997/56","pdf":"https://ijcai.org/proceedings/1997/0056.pdf","markdown":"https://ijcai.org/proceedings/1997/56.md","bibtex":"https://ijcai.org/proceedings/1997/bibtex/56","volume":{"slug":"1997","title":"Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 1997","url":"https://ijcai.org/proceedings/1997/","year":1997,"location":"Nagoya, Japan","dates":"","editors":"Martha E. Pollack","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":"Constraint Satisfaction","track":"Constraint Satisfaction","number":56,"pages":{"first":378,"last":382},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}