An exact algorithm for higher-dimensional orthogonal packing
Higher-dimensional orthogonal packing problems have a wide range of practical applications, including packing, cutting, and scheduling. Combining the use of our data structure for characterizing feasible packings with our new classes of lower bounds, and other heuristics, we develop a two-level tree...
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| creator | Fekete, Sandor P Schepers, Joerg van der Veen, Jan C |
| description | Higher-dimensional orthogonal packing problems have a wide range of practical
applications, including packing, cutting, and scheduling. Combining the use of
our data structure for characterizing feasible packings with our new classes of
lower bounds, and other heuristics, we develop a two-level tree search
algorithm for solving higher-dimensional packing problems to optimality.
Computational results are reported, including optimal solutions for all
two--dimensional test problems from recent literature.
This is the third in a series of articles describing new approaches to
higher-dimensional packing; see cs.DS/0310032 and cs.DS/0402044. |
| doi_str_mv | 10.48550/arxiv.cs/0604045 |
| format | Article |
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applications, including packing, cutting, and scheduling. Combining the use of
our data structure for characterizing feasible packings with our new classes of
lower bounds, and other heuristics, we develop a two-level tree search
algorithm for solving higher-dimensional packing problems to optimality.
Computational results are reported, including optimal solutions for all
two--dimensional test problems from recent literature.
This is the third in a series of articles describing new approaches to
higher-dimensional packing; see cs.DS/0310032 and cs.DS/0402044.</description><identifier>DOI: 10.48550/arxiv.cs/0604045</identifier><language>eng</language><subject>Computer Science - Data Structures and Algorithms</subject><creationdate>2006-04</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,776,881</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/cs/0604045$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.cs/0604045$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Fekete, Sandor P</creatorcontrib><creatorcontrib>Schepers, Joerg</creatorcontrib><creatorcontrib>van der Veen, Jan C</creatorcontrib><title>An exact algorithm for higher-dimensional orthogonal packing</title><description>Higher-dimensional orthogonal packing problems have a wide range of practical
applications, including packing, cutting, and scheduling. Combining the use of
our data structure for characterizing feasible packings with our new classes of
lower bounds, and other heuristics, we develop a two-level tree search
algorithm for solving higher-dimensional packing problems to optimality.
Computational results are reported, including optimal solutions for all
two--dimensional test problems from recent literature.
This is the third in a series of articles describing new approaches to
higher-dimensional packing; see cs.DS/0310032 and cs.DS/0402044.</description><subject>Computer Science - Data Structures and Algorithms</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2006</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNotj8tqwzAQRbXpoqT9gK6qH3CiVJoZGboJoS8IZJO9Gethi9pWkE1J_76QZnXP6nCuEE9btTYWQG24XNLP2s0bhcooA_fidTfJcGG3SB66XNLSjzLmIvvU9aFUPo1hmlOeeJC5LH3urnhm952m7kHcRR7m8HjblTi9v532n9Xh-PG13x0qRoKqNaaGGBQgGa9Mqy2RbXELHEOtvQFtnaodWrLBK2KN2r8gk8cWgSjqlXj-117zm3NJI5ffxs3N7Yb-AzUiQuI</recordid><startdate>20060411</startdate><enddate>20060411</enddate><creator>Fekete, Sandor P</creator><creator>Schepers, Joerg</creator><creator>van der Veen, Jan C</creator><scope>AKY</scope><scope>GOX</scope></search><sort><creationdate>20060411</creationdate><title>An exact algorithm for higher-dimensional orthogonal packing</title><author>Fekete, Sandor P ; Schepers, Joerg ; van der Veen, Jan C</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a675-b4495fe05674d04b38778b615afe93d4538c09c6878ed07a363d26a7d6b6577f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2006</creationdate><topic>Computer Science - Data Structures and Algorithms</topic><toplevel>online_resources</toplevel><creatorcontrib>Fekete, Sandor P</creatorcontrib><creatorcontrib>Schepers, Joerg</creatorcontrib><creatorcontrib>van der Veen, Jan C</creatorcontrib><collection>arXiv Computer Science</collection><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Fekete, Sandor P</au><au>Schepers, Joerg</au><au>van der Veen, Jan C</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>An exact algorithm for higher-dimensional orthogonal packing</atitle><date>2006-04-11</date><risdate>2006</risdate><abstract>Higher-dimensional orthogonal packing problems have a wide range of practical
applications, including packing, cutting, and scheduling. Combining the use of
our data structure for characterizing feasible packings with our new classes of
lower bounds, and other heuristics, we develop a two-level tree search
algorithm for solving higher-dimensional packing problems to optimality.
Computational results are reported, including optimal solutions for all
two--dimensional test problems from recent literature.
This is the third in a series of articles describing new approaches to
higher-dimensional packing; see cs.DS/0310032 and cs.DS/0402044.</abstract><doi>10.48550/arxiv.cs/0604045</doi><oa>free_for_read</oa></addata></record> |
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| subjects | Computer Science - Data Structures and Algorithms |
| title | An exact algorithm for higher-dimensional orthogonal packing |
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