{"title":"加权MAX-SAT问题的近似解","authors":"M. G. Resende, L. Pitsoulis, P. Pardalos","doi":"10.1090/dimacs/035/11","DOIUrl":null,"url":null,"abstract":"Computing the optimal solution to an instance of the weighted maximum satissability problem (MAX-SAT) is diicult even when each clause contains at most two literals. In this paper, we describe a greedy randomized adaptive search procedure (GRASP) for computing approximate solutions of weighted MAX-SAT problems. The heuristic is tested on a large set of test instances. Computational experience indicates the suitability of GRASP for this class of problems.","PeriodicalId":434373,"journal":{"name":"Satisfiability Problem: Theory and Applications","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"91","resultStr":"{\"title\":\"Approximate solution of weighted MAX-SAT problems using GRASP\",\"authors\":\"M. G. Resende, L. Pitsoulis, P. Pardalos\",\"doi\":\"10.1090/dimacs/035/11\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Computing the optimal solution to an instance of the weighted maximum satissability problem (MAX-SAT) is diicult even when each clause contains at most two literals. In this paper, we describe a greedy randomized adaptive search procedure (GRASP) for computing approximate solutions of weighted MAX-SAT problems. The heuristic is tested on a large set of test instances. Computational experience indicates the suitability of GRASP for this class of problems.\",\"PeriodicalId\":434373,\"journal\":{\"name\":\"Satisfiability Problem: Theory and Applications\",\"volume\":\"42 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"91\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Satisfiability Problem: Theory and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1090/dimacs/035/11\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Satisfiability Problem: Theory and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1090/dimacs/035/11","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Approximate solution of weighted MAX-SAT problems using GRASP
Computing the optimal solution to an instance of the weighted maximum satissability problem (MAX-SAT) is diicult even when each clause contains at most two literals. In this paper, we describe a greedy randomized adaptive search procedure (GRASP) for computing approximate solutions of weighted MAX-SAT problems. The heuristic is tested on a large set of test instances. Computational experience indicates the suitability of GRASP for this class of problems.