Article(id=1242118359110717697, tenantId=1146029695717560320, journalId=1146031591421210625, issueId=1242118341532386177, articleNumber=null, orderNo=null, doi=null, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1219334400000, receivedDateStr=2008-08-22, revisedDate=-2209017600000, revisedDateStr=1900-01-01, acceptedDate=null, acceptedDateStr=null, onlineDate=1176134400000, onlineDateStr=2007-04-10, pubDate=1176134400000, pubDateStr=2007-04-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1176134400000, onlineIssueDateStr=2007-04-10, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1774073694251, creator=sys-migrate, updateTime=1774073694251, updator=sys-migrate, issue=Issue{id=1242118341532386177, tenantId=1146029695717560320, journalId=1146031591421210625, year='2007', volume='25', issue='0707', pageStart='1', pageEnd='78', issueExtLink='null', onlineDate='null', pubDate='1176134400000', pubDateStr='2007-04-10', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=3, issueType=-1, specialIssue=null, createTime=1774073690062, creator='sys-migrate', updateTime=1774073690062, updator='sys-migrate', preIssue=null, nextIssue=null, articleTotal=null, ext=null, issueFiles=null, downloadFileDto=null}, startPage=65, endPage=70, ext={EN=ArticleExt(id=1242118361061065683, articleId=1242118359110717697, tenantId=1146029695717560320, journalId=1146031591421210625, language=EN, title=Genetic Algorithm for Item Selections in Retail Business, columnId=1242117518433780152, journalTitle=Science & Technology Review, columnName=研究报告, runingTitle=null, highlight=null, articleAbstract=A fundamental problem in retail business is selecting items with consideration of "cross-selling effect". Recent studies show that the problem is NP-hard. In this paper, the genetic algorithm is applied to this problem, and a quantitative analysis method for "cross-selling effect" is proposed, using quantitative association rules, and a newly developed data mining technique to identify quantitative affinities in large transaction databases. Based on the features of the genetic algorithm, a method of defining imprecise fitness function is proposed, which can be used for solving item selection problems with imprecision cross-selling effect., authors=null, authorsList=null, authorCompany=null, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=YT9roIvdNdt3YdgwS+cZRA==, pdfFileSize=531383, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1242118360650023887, articleId=1242118359110717697, tenantId=1146029695717560320, journalId=1146031591421210625, language=CN, title=零售业中商品选择问题的遗传算法研究, columnId=1242117343166399450, journalTitle=科技导报, columnName=研究报告, runingTitle=null, highlight=null, articleAbstract=选择经营哪些商品是零售业面对的一个重大决策问题，这个问题需要考虑到商品之间的交叉销售效果。最近的研究成果表明这一问题是NP难问题。采用定量关联规则技术来计算交叉销售效果，并提出一个面向商品选择问题的遗传算法。由于交叉销售效果是一个不精确的信息，根据遗传算法的要求，进一步研究了面向不精确信息的适应度函数，从而使遗传算法适用于基于交叉销售效果分析的商品选择问题。, authors=程岩, authorsList=程岩, authorCompany=复旦大学管理学院 信息管理与信息系统系 上海, correspAuthors=null, authorNote=null, correspAuthorsNote=程岩, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=OxOkBkQj2MpLWD8IXcGcIw==, pdfFileSize=531383, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null)}, authors=null, keywords=[Keyword(id=1242118359895049158, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1242118359110717697, language=CN, orderNo=1, keyword=遗传算法), Keyword(id=1242118359966352327, tenantId=1146029695717560320, 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