The Co-Printing Problem: A Packing Problem with a Color Constraint
The co-printing problem is a new variant of the bin-packing problem. It finds its origin in the printing of Tetra-bricks in the beverage industry. Combining different types of bricks in one printing pattern reduces the stock. With each brick, a number of colors are associated, and the total number o...
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Veröffentlicht in: | Operations research 2004-07, Vol.52 (4), p.623-638 |
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description | The co-printing problem is a new variant of the bin-packing problem. It finds its origin in the printing of Tetra-bricks in the beverage industry. Combining different types of bricks in one printing pattern reduces the stock. With each brick, a number of colors are associated, and the total number of colors for the whole pattern cannot exceed a given limit. We develop a branch-and-price algorithm to obtain proven optimal solutions. After introducing a Dantzig-Wolfe reformulation for the problem, we derive cutting planes to tighten the LP relaxation. We present heuristics and develop a branching scheme, avoiding complex pricing problem modifications. We present some further algorithmic enhancements, such as the implementation of dominance rules and a lower bound based on a combinatorial relaxation. Finally, we discuss computational results for real-life data sets. In addition to the introduction of a new bin-packing problem, this paper illustrates the complex balance in branch-and-price algorithms among using cutting planes, the branching scheme, and the tractability of the pricing problem. It also shows how dominance rules can be implemented in a branch-and-price framework, resulting in a substantial reduction in computation time. |
doi_str_mv | 10.1287/opre.1040.0112 |
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It finds its origin in the printing of Tetra-bricks in the beverage industry. Combining different types of bricks in one printing pattern reduces the stock. With each brick, a number of colors are associated, and the total number of colors for the whole pattern cannot exceed a given limit. We develop a branch-and-price algorithm to obtain proven optimal solutions. After introducing a Dantzig-Wolfe reformulation for the problem, we derive cutting planes to tighten the LP relaxation. We present heuristics and develop a branching scheme, avoiding complex pricing problem modifications. We present some further algorithmic enhancements, such as the implementation of dominance rules and a lower bound based on a combinatorial relaxation. Finally, we discuss computational results for real-life data sets. In addition to the introduction of a new bin-packing problem, this paper illustrates the complex balance in branch-and-price algorithms among using cutting planes, the branching scheme, and the tractability of the pricing problem. It also shows how dominance rules can be implemented in a branch-and-price framework, resulting in a substantial reduction in computation time.</description><identifier>ISSN: 0030-364X</identifier><identifier>EISSN: 1526-5463</identifier><identifier>DOI: 10.1287/opre.1040.0112</identifier><identifier>CODEN: OPREAI</identifier><language>eng</language><publisher>Linthicum: INFORMS</publisher><subject>Algorithms ; Analysis ; applications ; branch-and-price ; Bricks ; Cardinality ; Color-printing ; Commercial printing industry ; Datasets ; decomposition ; Heuristic ; Heuristics ; Incumbents ; integer ; Integer programming ; Integers ; Inventory control ; inventory/production ; Methods ; Objective functions ; Optimal solutions ; Optimization ; packing ; Packing problem ; Pattern-making ; Printing ; Printing industry ; Production planning ; programming ; Studies ; Technology application</subject><ispartof>Operations research, 2004-07, Vol.52 (4), p.623-638</ispartof><rights>Copyright 2004 INFORMS</rights><rights>COPYRIGHT 2004 Institute for Operations Research and the Management Sciences</rights><rights>Copyright Institute for Operations Research and the Management Sciences Jul/Aug 2004</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c432t-f7ffff041e805c96adf490d967749f628c7718fc5865ef2de2106cb551c026c33</citedby><cites>FETCH-LOGICAL-c432t-f7ffff041e805c96adf490d967749f628c7718fc5865ef2de2106cb551c026c33</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/30036612$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://pubsonline.informs.org/doi/full/10.1287/opre.1040.0112$$EHTML$$P50$$Ginforms$$H</linktohtml><link.rule.ids>314,776,780,799,3678,27903,27904,57995,58228,62592</link.rule.ids></links><search><creatorcontrib>Peeters, Marc</creatorcontrib><creatorcontrib>Degraeve, Zeger</creatorcontrib><title>The Co-Printing Problem: A Packing Problem with a Color Constraint</title><title>Operations research</title><description>The co-printing problem is a new variant of the bin-packing problem. It finds its origin in the printing of Tetra-bricks in the beverage industry. Combining different types of bricks in one printing pattern reduces the stock. With each brick, a number of colors are associated, and the total number of colors for the whole pattern cannot exceed a given limit. We develop a branch-and-price algorithm to obtain proven optimal solutions. After introducing a Dantzig-Wolfe reformulation for the problem, we derive cutting planes to tighten the LP relaxation. We present heuristics and develop a branching scheme, avoiding complex pricing problem modifications. We present some further algorithmic enhancements, such as the implementation of dominance rules and a lower bound based on a combinatorial relaxation. Finally, we discuss computational results for real-life data sets. In addition to the introduction of a new bin-packing problem, this paper illustrates the complex balance in branch-and-price algorithms among using cutting planes, the branching scheme, and the tractability of the pricing problem. It also shows how dominance rules can be implemented in a branch-and-price framework, resulting in a substantial reduction in computation time.</description><subject>Algorithms</subject><subject>Analysis</subject><subject>applications</subject><subject>branch-and-price</subject><subject>Bricks</subject><subject>Cardinality</subject><subject>Color-printing</subject><subject>Commercial printing industry</subject><subject>Datasets</subject><subject>decomposition</subject><subject>Heuristic</subject><subject>Heuristics</subject><subject>Incumbents</subject><subject>integer</subject><subject>Integer programming</subject><subject>Integers</subject><subject>Inventory control</subject><subject>inventory/production</subject><subject>Methods</subject><subject>Objective functions</subject><subject>Optimal solutions</subject><subject>Optimization</subject><subject>packing</subject><subject>Packing problem</subject><subject>Pattern-making</subject><subject>Printing</subject><subject>Printing 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Zeger</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The Co-Printing Problem: A Packing Problem with a Color Constraint</atitle><jtitle>Operations research</jtitle><date>2004-07-01</date><risdate>2004</risdate><volume>52</volume><issue>4</issue><spage>623</spage><epage>638</epage><pages>623-638</pages><issn>0030-364X</issn><eissn>1526-5463</eissn><coden>OPREAI</coden><abstract>The co-printing problem is a new variant of the bin-packing problem. It finds its origin in the printing of Tetra-bricks in the beverage industry. Combining different types of bricks in one printing pattern reduces the stock. With each brick, a number of colors are associated, and the total number of colors for the whole pattern cannot exceed a given limit. We develop a branch-and-price algorithm to obtain proven optimal solutions. After introducing a Dantzig-Wolfe reformulation for the problem, we derive cutting planes to tighten the LP relaxation. We present heuristics and develop a branching scheme, avoiding complex pricing problem modifications. We present some further algorithmic enhancements, such as the implementation of dominance rules and a lower bound based on a combinatorial relaxation. Finally, we discuss computational results for real-life data sets. In addition to the introduction of a new bin-packing problem, this paper illustrates the complex balance in branch-and-price algorithms among using cutting planes, the branching scheme, and the tractability of the pricing problem. It also shows how dominance rules can be implemented in a branch-and-price framework, resulting in a substantial reduction in computation time.</abstract><cop>Linthicum</cop><pub>INFORMS</pub><doi>10.1287/opre.1040.0112</doi><tpages>16</tpages></addata></record> |
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subjects | Algorithms Analysis applications branch-and-price Bricks Cardinality Color-printing Commercial printing industry Datasets decomposition Heuristic Heuristics Incumbents integer Integer programming Integers Inventory control inventory/production Methods Objective functions Optimal solutions Optimization packing Packing problem Pattern-making Printing Printing industry Production planning programming Studies Technology application |
title | The Co-Printing Problem: A Packing Problem with a Color Constraint |
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