[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-seo-265225-105":3,"detail-sidebar-cat-0-en-105":81,"doc-detail-265225-en":131},{"code":4,"msg":5,"data":6},0,"ok",{"site_id":7,"language":8,"slug":9,"title":10,"keywords":11,"description":12,"schema_data":13,"social_meta":74,"head_meta":76,"extra_data":78,"updated_unix":80},105,"en","local-search-algorithms-for-sat-an-empirical-evaluation","Local Search Algorithms for SAT - An Empirical Evaluation","","Local search algorithms are widely used to tackle hard combinatorial optimization tasks, and for SAT many leading approaches rely on stochastic local search. This work studies two major SAT local-search families, GSAT and WalkSAT, through a benchmark combining instances from randomized distributions and SAT-encoded problems from diverse application domains. The analysis compares performance, examines robustness as algorithm parameters and problem-dependent characteristics change, and identifies a fundamental weakness in top-performing variants together with a way to address it.",{"@graph":14,"@context":73},[15,34,56],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/research-report/","Research & Report",3,{"item":32,"name":10,"@type":21,"position":33},"https://docshare.wps.com/document/local-search-algorithms-for-sat-an-empirical-evaluation/265225/",4,{"url":32,"name":10,"@type":35,"image":36,"author":41,"headline":10,"publisher":44,"fileFormat":47,"inLanguage":8,"description":12,"dateModified":48,"datePublished":49,"encodingFormat":47,"isAccessibleForFree":50,"interactionStatistic":51},"DigitalDocument",{"url":37,"@type":38,"width":39,"height":40},"https://docshare.wps.com/thumbnails/local-search-algorithms-for-sat-an-empirical-evaluation/265225.png","ImageObject",300,407,{"name":42,"@type":43},"Chumphorn","Person",{"url":19,"name":45,"@type":46},"DocShare","Organization","application/pdf","2026-10-27","2026-09-14",true,{"@type":52,"interactionType":53,"userInteractionCount":55},"InteractionCounter",{"@type":54},"ViewAction",11,{"@type":57,"mainEntity":58},"FAQPage",[59,65,69],{"name":60,"@type":61,"acceptedAnswer":62},"What problem does the document address and why is it important?","Question",{"text":63,"@type":64},"The document addresses the satisfiability problem in propositional logic (SAT), which asks whether a given formula has a satisfying assignment. It is central across computer science because SAT is a fundamental conceptually simple NP-complete problem and appears in many research areas.","Answer",{"name":66,"@type":61,"acceptedAnswer":67},"Which algorithm families are compared in the empirical evaluation?",{"text":68,"@type":64},"The study focuses on two well-known stochastic local search architectures for SAT: GSAT and WalkSAT. These families are selected due to their major influence in SAT local search and the availability of efficient optimized implementations.",{"name":70,"@type":61,"acceptedAnswer":71},"What methodology is used to evaluate performance more deeply than basic statistics?",{"text":72,"@type":64},"The document uses a refined approach based on measuring and analyzing run-time distributions (RTDs) per individual SAT instance. This separates randomness from instance generation and the algorithm’s inherent stochasticity, and enables analysis of solution probabilities under time limits and stagnation behavior.","https://schema.org",{"og:url":32,"og:type":75,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":77,"canonical":32},"index,follow",{"doc_id":79,"site_id":7},265225,1789393480,{"code":4,"msg":82,"data":83},"success",[84,88,92,96,101,106,111,115,120,123,127],{"id":22,"doc_module":4,"doc_module_name":25,"category_name":85,"show_sort_weight":86,"slug":87},"Story & Novel",90,"story-novel",{"id":26,"doc_module":4,"doc_module_name":25,"category_name":89,"show_sort_weight":90,"slug":91},"Literature",80,"literature",{"id":33,"doc_module":4,"doc_module_name":25,"category_name":93,"show_sort_weight":94,"slug":95},"Exam",70,"exam",{"id":97,"doc_module":4,"doc_module_name":25,"category_name":98,"show_sort_weight":99,"slug":100},5,"Comic",60,"comic",{"id":102,"doc_module":4,"doc_module_name":25,"category_name":103,"show_sort_weight":104,"slug":105},6,"Technology",50,"technology",{"id":107,"doc_module":4,"doc_module_name":25,"category_name":108,"show_sort_weight":109,"slug":110},7,"Healthcare",40,"healthcare",{"id":112,"doc_module":4,"doc_module_name":25,"category_name":29,"show_sort_weight":113,"slug":114},8,30,"research-report",{"id":116,"doc_module":4,"doc_module_name":25,"category_name":117,"show_sort_weight":118,"slug":119},9,"Religion & Spirituality",20,"religion-spirituality",{"id":118,"doc_module":4,"doc_module_name":25,"category_name":121,"show_sort_weight":118,"slug":122},"World Cup","world-cup",{"id":124,"doc_module":4,"doc_module_name":25,"category_name":125,"show_sort_weight":124,"slug":126},10,"Lifestyle","lifestyle",{"id":128,"doc_module":4,"doc_module_name":25,"category_name":129,"show_sort_weight":97,"slug":130},19,"General","general",{"code":4,"msg":82,"data":132},{"doc_id":79,"user_id":133,"nickname":42,"user_avatar":134,"doc_module":4,"category_id":112,"category_name":29,"doc_title":10,"doc_description":12,"doc_content":135,"file_id":136,"file_url":137,"file_type":138,"file_size":139,"view_count":55,"is_deleted":4,"is_public":22,"is_downloadable":22,"audit_status":22,"page_count":140,"language":141,"language_code":8,"site_id":7,"html_lang":8,"table_of_contents":142,"faqs":143,"seo_title":144,"seo_description":12,"update_tm":80,"read_time":145,"preview_page_count":4},2336475401981,"https://ap-avatar.wpscdn.com/avatar/22000c94efd8d5204d?x-image-process=image/resize,m_fixed,w_180,h_180&k=1786935347598174694","Local Search Algorithms for SAT: An Empirical Evaluation  \nHolger H. Hoos ([hoos@cs.ubc.ca](hoos@cs.ubc.ca)) Department of Computer Science University of British Columbia  \nVancouver, Canada  \nThomas Stützle􀀀 ([tstutzle@ulb.ac.be](tstutzle@ulb.ac.be)) IRIDIA, Université Libre de Bruxelles  \nBrussels, Belgium  \nAbstract. Local search algorithms are among the standard methods for solving hard combinatorial problems from various areas ofArtificial Intelligence and Operations Research. For SAT, some of the most successful and powerful algorithms are based on stochastic local search and in the past 10 years a large number of such algorithms have been proposed and investigated. In this article, we focus on two particularly well-known families of local search algorithms for SAT, the GSAT and WalkSAT architectures. We present a detailed comparative analysis of these algorithms’ performance using a benchmark set which contains instances from randomised distributions as well as SAT-encoded problems from various domains. We also investigate the robustness of the observed performance characteristics as algorithm-dependent and problem-dependent parameters are changed. Our empirical analysis gives a very detailed picture of the algorithms’ performance for various domains of SAT problems; it also reveals a fundamental weakness in some of the best-performing algorithms and shows how this can be overcome.  \nKeywords: SAT, Stochastic Local Search, Empirical Evaluation, Run-time Distributions, Robustness  \n1. Introduction  \nThe satisfiability problem in propositional logic (SAT) is the task to decide for a given propositional formula whether it has a model. This problem plays a prominent role in various areas of computer science, as it is one of the conceptually simplest ✁✂ -complete problems. Local search approaches for SAT became prominent in 1992, when independently Selman, Levesque, and Mitchell [60] as well as Gu [27] introduced algorithms based on stochastic local hill-climbing which could be shown to outperform state-of-the-art systematic SAT algorithms like ASAT [13] on a variety of hard subclasses of SAT [4, 59] . Since then, numerous other stochastic local search (SLS) schemes for SAT have been proposed. To date, state-of-the-art SLS algorithms can solve hard SAT problems with up to several thousand variables, including SAT-encoded problems from other domains. But because of their inherent randomness, the behaviour of SLS algorithms is generally difficult to analyse theoretically and even in the cases where theoretical results do  \n☎ On leave from FG Intellektik, TU Darmstadt, Germany  \n © 2000 KluwerAcademic Publishers. Printed in the Netherlands.  \nsat2000 .tex; 14/03/2000; 12:10; p .1  \n2 Hoos and Stützle  \nexist, their practical applicability is often very limited. Given this situation, the performance of SLS algorithms is usually analysed using empirical methodology.  \nIn this paper, we empirically analyse the behaviour of algorithms from the GSAT and WalkSAT architectures of SLS algorithms for SAT. These algorithm families were chosen for two reasons: Firstly, they provided a major driving force in the development and application of SLS algorithms for SAT. Secondly, for most algorithms from these families, very efficient, thoroughly optimised implementations are available which could easily be modified and extended to cover some more variants and to yield a sufficiently coherent framework for practically conducting experiments. Although our empirical methodology allows us to abstract from machine-and implementation-specific details of algorithmic performance, some of our analyses are so computationally expensive that efficient implementations are indispensable.  \nOur empirical analysis addresses several important issues. Maybe the most straightforward question to ask is how the performance of different algorithms compares across a range of problem instances from different subclasses of SAT. But furthermore, as the behaviour of these algo","cbCairuFzRpXBAPp","https://ap.wps.com/l/cbCairuFzRpXBAPp","pdf",796399,62,"English","# Introduction\n## SAT and local search overview\n## GSAT and WalkSAT focus\n## Empirical methodology using runtime distributions","[{\"question\":\"What problem does the document address and why is it important?\",\"answer\":\"The document addresses the satisfiability problem in propositional logic (SAT), which asks whether a given formula has a satisfying assignment. It is central across computer science because SAT is a fundamental conceptually simple NP-complete problem and appears in many research areas.\"},{\"question\":\"Which algorithm families are compared in the empirical evaluation?\",\"answer\":\"The study focuses on two well-known stochastic local search architectures for SAT: GSAT and WalkSAT. These families are selected due to their major influence in SAT local search and the availability of efficient optimized implementations.\"},{\"question\":\"What methodology is used to evaluate performance more deeply than basic statistics?\",\"answer\":\"The document uses a refined approach based on measuring and analyzing run-time distributions (RTDs) per individual SAT instance. This separates randomness from instance generation and the algorithm’s inherent stochasticity, and enables analysis of solution probabilities under time limits and stagnation behavior.\"}]","Local Search Algorithms for SAT - An Empirical Evaluation | PDF",156]