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<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.0 20120330//EN" "JATS-journalpublishing1.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" article-type="research-article"><front><journal-meta><journal-id journal-id-type="publisher-id">INFORMATICA</journal-id><journal-title-group><journal-title>Informatica</journal-title></journal-title-group><issn pub-type="epub">0868-4952</issn><issn pub-type="ppub">0868-4952</issn><publisher><publisher-name>VU</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="publisher-id">INF41-212</article-id><article-id pub-id-type="doi">10.3233/INF-1993-41-212</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research article</subject></subj-group></article-categories><title-group><article-title>A computational comparison of local search heuristics for solving quadratic assignment problems</article-title></title-group><contrib-group><contrib contrib-type="Author"><name><surname>Pardalos</surname><given-names>Panos M.</given-names></name><xref ref-type="aff" rid="j_INFORMATICA_aff_000"/></contrib><contrib contrib-type="Author"><name><surname>Murthy</surname><given-names>Kowta A.</given-names></name><xref ref-type="aff" rid="j_INFORMATICA_aff_001"/></contrib><contrib contrib-type="Author"><name><surname>Harrison</surname><given-names>Terry P.</given-names></name><xref ref-type="aff" rid="j_INFORMATICA_aff_001"/></contrib><aff id="j_INFORMATICA_aff_000">University of Florida, Gainesville, FL 32611</aff><aff id="j_INFORMATICA_aff_001">The Pennsylvania State University, University Park, PA 16802</aff></contrib-group><pub-date pub-type="epub"><day>01</day><month>01</month><year>1993</year></pub-date><volume>4</volume><issue>1-2</issue><fpage>172</fpage><lpage>187</lpage><abstract><p>It is well known that, in general, exact algorithms for the Quadratic Assignment Problem (QAP) cannot solve problems of size N&gt;15. Therefore, it is necessary to use heuristic approaches for solving large-scale QAPs. In this paper, we consider a class of heuristic approaches based on local search criteria. In particular, we selected four algorithms; CRAFT, Simulated Annealing, TABU search and the Graph Partitioning (GP) approach and studied their relative performance in terms of the quality of solutions and CPU times. All of these algorithms performed roughly the same, based on the results of two sets of test problems executed on an IBM ES/3090-600S computer.</p></abstract><kwd-group><label>Keywords</label><kwd>quadratic assignment</kwd><kwd>local search</kwd><kwd>tabu search</kwd><kwd>simulated annealing</kwd><kwd>graph positioning</kwd><kwd>testing</kwd></kwd-group></article-meta></front></article>