Online Dial-a-Ride Problems: Minimizing the Completion Time?
We consider the following online dial-a-ride problem (OlDarp): Objects are to be transported between points in a metric space. Transportation requests arrive online, specifying the objects to be transported and the corresponding source and destination. These requests are to be handled by a server wh...
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description | We consider the following online dial-a-ride problem (OlDarp): Objects are to be transported between points in a metric space. Transportation requests arrive online, specifying the objects to be transported and the corresponding source and destination. These requests are to be handled by a server which starts its work at a designated origin and which picks up and drops objects at their sources and destinations. The server can move at constant unit speed. After the end of its service the server returns to its start in the origin. The goal of OlDarp is to come up with a transportation schedule for the server which finishes as early as possible, i.e., which minimizes the makespan.
We analyze several competitive algorithms for OlDarp and establish tight competitiveness results. The first two algorithms, REPLAN and IGNORE are very simple and natural: REPLAN completely discards its (preliminary) schedule and recomputes a new one when a new request arrives. IGNORE always runs a (locally optimal) schedule for a set of known requests and ignores all new requests until this schedule is completed. We show that both strategies, REPLAN and IGNORE, are 5/2-competitive.
We then present a somewhat less natural strategy SMARTSTART, which in contrast to the other two strategies may leave the server idle from time to time although unserved requests are known. The SMARTSTART-algorithm has an improved competitive ratio of 2, which matches our lower bound. |
doi_str_mv | 10.1007/3-540-46541-3_53 |
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We analyze several competitive algorithms for OlDarp and establish tight competitiveness results. The first two algorithms, REPLAN and IGNORE are very simple and natural: REPLAN completely discards its (preliminary) schedule and recomputes a new one when a new request arrives. IGNORE always runs a (locally optimal) schedule for a set of known requests and ignores all new requests until this schedule is completed. We show that both strategies, REPLAN and IGNORE, are 5/2-competitive.
We then present a somewhat less natural strategy SMARTSTART, which in contrast to the other two strategies may leave the server idle from time to time although unserved requests are known. The SMARTSTART-algorithm has an improved competitive ratio of 2, which matches our lower bound.</description><identifier>ISSN: 0302-9743</identifier><identifier>ISBN: 9783540671411</identifier><identifier>ISBN: 3540671412</identifier><identifier>EISSN: 1611-3349</identifier><identifier>EISBN: 9783540465416</identifier><identifier>EISBN: 3540465413</identifier><identifier>DOI: 10.1007/3-540-46541-3_53</identifier><identifier>OCLC: 45578647</identifier><identifier>LCCallNum: QA75.5 -- .S956 2000eb</identifier><language>eng</language><publisher>Germany: Springer Berlin / Heidelberg</publisher><subject>Algorithmics. Computability. Computer arithmetics ; Applied sciences ; Competitive Algorithm ; Competitive Ratio ; Completion Time ; Computer science; control theory; systems ; Exact sciences and technology ; Flows in networks. Combinatorial problems ; Online Algorithm ; Operational research and scientific management ; Operational research. Management science ; Setup Cost ; Theoretical computing</subject><ispartof>Lecture notes in computer science, 2000, Vol.1770, p.639-650</ispartof><rights>Springer-Verlag Berlin Heidelberg 2000</rights><rights>2000 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c360t-cceac06fa933a28c31e240f479fb8d9bce4c8c3436ba6a6d01f5347d9446475a3</citedby><relation>Lecture Notes in Computer Science</relation></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Uhttps://ebookcentral.proquest.com/covers/3061677-l.jpg</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/3-540-46541-3_53$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/3-540-46541-3_53$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>309,310,777,778,782,787,788,791,27908,38238,41425,42494</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=1177432$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><contributor>Reichel, Horst</contributor><contributor>Tison, Sophie</contributor><contributor>Reichel, Horst</contributor><contributor>Tison, Sophie</contributor><creatorcontrib>Ascheuer, Norbert</creatorcontrib><creatorcontrib>Krumke, Sven O.</creatorcontrib><creatorcontrib>Rambau, Jörg</creatorcontrib><title>Online Dial-a-Ride Problems: Minimizing the Completion Time?</title><title>Lecture notes in computer science</title><description>We consider the following online dial-a-ride problem (OlDarp): Objects are to be transported between points in a metric space. Transportation requests arrive online, specifying the objects to be transported and the corresponding source and destination. These requests are to be handled by a server which starts its work at a designated origin and which picks up and drops objects at their sources and destinations. The server can move at constant unit speed. After the end of its service the server returns to its start in the origin. The goal of OlDarp is to come up with a transportation schedule for the server which finishes as early as possible, i.e., which minimizes the makespan.
We analyze several competitive algorithms for OlDarp and establish tight competitiveness results. The first two algorithms, REPLAN and IGNORE are very simple and natural: REPLAN completely discards its (preliminary) schedule and recomputes a new one when a new request arrives. IGNORE always runs a (locally optimal) schedule for a set of known requests and ignores all new requests until this schedule is completed. We show that both strategies, REPLAN and IGNORE, are 5/2-competitive.
We then present a somewhat less natural strategy SMARTSTART, which in contrast to the other two strategies may leave the server idle from time to time although unserved requests are known. The SMARTSTART-algorithm has an improved competitive ratio of 2, which matches our lower bound.</description><subject>Algorithmics. Computability. Computer arithmetics</subject><subject>Applied sciences</subject><subject>Competitive Algorithm</subject><subject>Competitive Ratio</subject><subject>Completion Time</subject><subject>Computer science; control theory; systems</subject><subject>Exact sciences and technology</subject><subject>Flows in networks. Combinatorial problems</subject><subject>Online Algorithm</subject><subject>Operational research and scientific management</subject><subject>Operational research. Management science</subject><subject>Setup Cost</subject><subject>Theoretical computing</subject><issn>0302-9743</issn><issn>1611-3349</issn><isbn>9783540671411</isbn><isbn>3540671412</isbn><isbn>9783540465416</isbn><isbn>3540465413</isbn><fulltext>true</fulltext><rsrctype>book_chapter</rsrctype><creationdate>2000</creationdate><recordtype>book_chapter</recordtype><recordid>eNqNkElPxDAMhcMqRjB3jj1wDcS1mzQICaFhlUAgBOcozaQQ6DI05QC_ngwgzuTi6D1_lv0Y2wWxD0KoA-QFCU6yIOBoClxhU61KTOK3JlfZBCQkD0mv_XlSAQGss4lAkXOtCDfZFhWFKiWpLTaN8UWkhyBAw4Qd3XZN6Hx2GmzDLb8Pc5_dDX3V-DYeZjehC234DN1TNj77bNa3i8aPoe-yh9D64x22Udsm-ulv3WaP52cPs0t-fXtxNTu55g6lGLlz3joha6sRbV46BJ-TqEnpuirnunKeXFIJZWWllXMBdYGk5poo7VxY3GZ7P3MXNjrb1IPtXIhmMYTWDh8GQKUz89S2_9MWk9M9-cFUff8aDQizDNSkEEmY7_CWf0wA_c4d-rd3H0fjl4Tz3TjYxj3bxeiHaCQtI01kqY38P4ZCglQqYWXCcvwCRyyDrg</recordid><startdate>20000101</startdate><enddate>20000101</enddate><creator>Ascheuer, Norbert</creator><creator>Krumke, Sven O.</creator><creator>Rambau, Jörg</creator><general>Springer Berlin / Heidelberg</general><general>Springer Berlin Heidelberg</general><general>Springer</general><scope>FFUUA</scope><scope>IQODW</scope></search><sort><creationdate>20000101</creationdate><title>Online Dial-a-Ride Problems: Minimizing the Completion Time?</title><author>Ascheuer, Norbert ; Krumke, Sven O. ; Rambau, Jörg</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c360t-cceac06fa933a28c31e240f479fb8d9bce4c8c3436ba6a6d01f5347d9446475a3</frbrgroupid><rsrctype>book_chapters</rsrctype><prefilter>book_chapters</prefilter><language>eng</language><creationdate>2000</creationdate><topic>Algorithmics. Computability. Computer arithmetics</topic><topic>Applied sciences</topic><topic>Competitive Algorithm</topic><topic>Competitive Ratio</topic><topic>Completion Time</topic><topic>Computer science; control theory; systems</topic><topic>Exact sciences and technology</topic><topic>Flows in networks. Combinatorial problems</topic><topic>Online Algorithm</topic><topic>Operational research and scientific management</topic><topic>Operational research. Management science</topic><topic>Setup Cost</topic><topic>Theoretical computing</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ascheuer, Norbert</creatorcontrib><creatorcontrib>Krumke, Sven O.</creatorcontrib><creatorcontrib>Rambau, Jörg</creatorcontrib><collection>ProQuest Ebook Central - Book Chapters - Demo use only</collection><collection>Pascal-Francis</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ascheuer, Norbert</au><au>Krumke, Sven O.</au><au>Rambau, Jörg</au><au>Reichel, Horst</au><au>Tison, Sophie</au><au>Reichel, Horst</au><au>Tison, Sophie</au><format>book</format><genre>bookitem</genre><ristype>CHAP</ristype><atitle>Online Dial-a-Ride Problems: Minimizing the Completion Time?</atitle><btitle>Lecture notes in computer science</btitle><seriestitle>Lecture Notes in Computer Science</seriestitle><date>2000-01-01</date><risdate>2000</risdate><volume>1770</volume><spage>639</spage><epage>650</epage><pages>639-650</pages><issn>0302-9743</issn><eissn>1611-3349</eissn><isbn>9783540671411</isbn><isbn>3540671412</isbn><eisbn>9783540465416</eisbn><eisbn>3540465413</eisbn><abstract>We consider the following online dial-a-ride problem (OlDarp): Objects are to be transported between points in a metric space. Transportation requests arrive online, specifying the objects to be transported and the corresponding source and destination. These requests are to be handled by a server which starts its work at a designated origin and which picks up and drops objects at their sources and destinations. The server can move at constant unit speed. After the end of its service the server returns to its start in the origin. The goal of OlDarp is to come up with a transportation schedule for the server which finishes as early as possible, i.e., which minimizes the makespan.
We analyze several competitive algorithms for OlDarp and establish tight competitiveness results. The first two algorithms, REPLAN and IGNORE are very simple and natural: REPLAN completely discards its (preliminary) schedule and recomputes a new one when a new request arrives. IGNORE always runs a (locally optimal) schedule for a set of known requests and ignores all new requests until this schedule is completed. We show that both strategies, REPLAN and IGNORE, are 5/2-competitive.
We then present a somewhat less natural strategy SMARTSTART, which in contrast to the other two strategies may leave the server idle from time to time although unserved requests are known. The SMARTSTART-algorithm has an improved competitive ratio of 2, which matches our lower bound.</abstract><cop>Germany</cop><pub>Springer Berlin / Heidelberg</pub><doi>10.1007/3-540-46541-3_53</doi><oclcid>45578647</oclcid><tpages>12</tpages></addata></record> |
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subjects | Algorithmics. Computability. Computer arithmetics Applied sciences Competitive Algorithm Competitive Ratio Completion Time Computer science control theory systems Exact sciences and technology Flows in networks. Combinatorial problems Online Algorithm Operational research and scientific management Operational research. Management science Setup Cost Theoretical computing |
title | Online Dial-a-Ride Problems: Minimizing the Completion Time? |
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