Best-First Search Methods for Constrained Two-Dimensional Cutting Stock Problems
Best-first search is a widely used problem solving technique in the field of artificial intelligence. The method has useful applications in operations research as well. Here we describe an application to constrained two-dimensional cutting stock problems of the following type: A stock rectangle S of...
Saved in:
| Published in | Operations research Vol. 41; no. 4; pp. 768 - 776 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Linthicum, MD
INFORMS
01.07.1993
Operations Research Society of America Institute for Operations Research and the Management Sciences |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0030-364X 1526-5463 |
| DOI | 10.1287/opre.41.4.768 |
Cover
| Abstract | Best-first search is a widely used problem solving technique in the field of artificial intelligence. The method has useful applications in operations research as well. Here we describe an application to constrained two-dimensional cutting stock problems of the following type: A stock rectangle S of dimensions ( L , W ) is supplied. There are n types of demanded rectangles r 1 , r 2 , ..., r n , with the i th type having length l i , width w i , value v i , and demand constraint b i . It is required to produce, from the stock rectangle S , a i copies of r i , 1 i n , to maximize a 1 v 1 + a 2 v 2 + · + a n v n subject to the constraints a i b i . Only orthogonal guillotine cuts are permitted. All parameters are integers. A best-first tree search algorithm based on Wang's bottom-up approach is described that guarantees optimal solutions and is more efficient than existing methods. |
|---|---|
| AbstractList | Best-first search is a widely used problem solving technique in the field of artificial intelligence. The method has useful applications in operations research as well. Here we describe an application to constrained two-dimensional cutting stock problems of the following type: A stock rectangle
S
of dimensions (
L
,
W
) is supplied. There are
n
types of demanded rectangles
r
1
,
r
2
, …,
r
n
, with the
i
th type having length
l
i
, width
w
i
, value
v
i
, and demand constraint
b
i
. It is required to produce, from the stock rectangle
S
,
a
i
copies of
r
i
, 1 ≤
i
≤
n
, to maximize
a
1
v
1
+
a
2
v
2
+ · +
a
n
v
n
subject to the constraints
a
i
≤
b
i
. Only orthogonal guillotine cuts are permitted. All parameters are integers. A best-first tree search algorithm based on Wang's bottom-up approach is described that guarantees optimal solutions and is more efficient than existing methods. Best-first search is a widely used problem-solving technique in the field of artificial intelligence. The method has useful applications in operations research as well. An application of the method to the constrained 2-dimensional cutting stock problem (CTCSP) is described. In the CTCSP a single rectangular stock sheet must be cut in an optimal way into required rectangles of smaller size without violating specified constraints. All cuts must be orthogonal, meaning parallel to one side of the rectangle, and any cut must also be a guillotine cut, meaning it must run from end to end on the rectangle being cut. All parameters are integers. The analysis describes a best-first tree search algorithm based on Wang's (1983) bottom-up approach. The proposed algorithm guarantees optimal solutions and is more effective than existing methods. Best-first search is a widely used problem solving technique in the field of artificial intelligence. The method has useful applications in operations research as well. Here we describe an application to constrained two-dimensional cutting stock problems of the following type: A stock rectangle S of dimensions ( L , W ) is supplied. There are n types of demanded rectangles r 1 , r 2 , ..., r n , with the i th type having length l i , width w i , value v i , and demand constraint b i . It is required to produce, from the stock rectangle S , a i copies of r i , 1 i n , to maximize a 1 v 1 + a 2 v 2 + · + a n v n subject to the constraints a i b i . Only orthogonal guillotine cuts are permitted. All parameters are integers. A best-first tree search algorithm based on Wang's bottom-up approach is described that guarantees optimal solutions and is more efficient than existing methods. Best-first search is a widely used problem solving technique in the field of artificial intelligence. The method has useful applications in operations research as well. Here we describe an application to constrained two-dimensional cutting stock problems of the following type. A stock rectangle S of dimensions (L, W) is supplied. There are n types of demanded rectangles r sub(1), r sub(2),...r sub(n) with the ith type having length l sub(1), width w sub(i), value v sub(1), and demand constraint b sub(j). It is required to produce, from the stock rectangle S, a sub(j) copies of r sub(i) 1 < i < n. to maximize a sub(1)v sub(1) + a sub(2)v sub(1) + a sub(2)v sub(2) + ... + a sub(n)v sub(n) subject to the constraints a sub(i) less than or equal to b sub(r). Only orthogonal guillotine cuts are permitted. All parameters are integers. A best-first tree search algorithm based on Wang's bottom-up approach is described that guarantees optimal solutions and is more efficient than existing methods. Best-first search is a widely used problem solving technique in the field of artificial intelligence. The method has useful applications in operations research as well. Here we describe an application to constrained two-dimensional cutting stock problems of the following type: A stock rectangle S of dimensions (L, W) is supplied. There are n types of demanded rectangles r1,r2,...,rn, with the ith type having length li, width wi, value vi, and demand constraint bi. It is required to produce, from the stock rectangle S, aicopies of ri, 1≤ i≤ n, to maximize a1v1+a2v2+... +anvnsubject to the constraints ai≤ bi. Only orthogonal guillotine cuts are permitted. All parameters are integers. A best-first tree search algorithm based on Wang's bottom-up approach is described that guarantees optimal solutions and is more efficient than existing methods. Best-first search is a widely used problem solving technique in the field of artificial intelligence. The method has useful applications in operations research as well. Here we describe an application to constrained two-dimensional cutting stock problems of the following type: A stock rectangle S of dimensions (L, W) is supplied. There are n types of demanded rectangles r 1 , r 2 , …, r n , with the ith type having length l i , width w i , value v i , and demand constraint b i . It is required to produce, from the stock rectangle S, a i copies of r i , 1 ≤ i ≤ n, to maximize a 1 v 1 + a 2 v 2 + · + a n v n subject to the constraints a i ≤ b i . Only orthogonal guillotine cuts are permitted. All parameters are integers. A best-first tree search algorithm based on Wang's bottom-up approach is described that guarantees optimal solutions and is more efficient than existing methods. |
| Author | Viswanathan, K. V Bagchi, A |
| Author_xml | – sequence: 1 fullname: Viswanathan, K. V – sequence: 2 fullname: Bagchi, A |
| BackLink | http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=3808987$$DView record in Pascal Francis |
| BookMark | eNqFkc1vEzEQxS1UJNLCkROXFaCe2OBZf-6xBApIRVRqkbitHGe2cdi1g-2o6n-PVwlUqlRx8uH93oznvWNy5INHQl4CnUOj1fuwjTjnMOdzJfUTMgPRyFpwyY7IjFJGayb5z2fkOKUNpbQVUszI5QdMuT53MeXqCk206-ob5nVYpaoPsVoEn3I0zuOqur4N9Uc3ok8ueDNUi13Ozt9UVznYX9VlDMsBx_ScPO3NkPDF4T0hP84_XS--1BffP39dnF3UlgmWa90DRatXPTcMwTYWl2AobwWwXisuLPCmlb0RzKoWEFE1CjkuRQ9S4LJhJ-R0P3cbw-9dOaIbXbI4DMZj2KWuES1vpFIFfP0A3IRdLAcUBlpQFLQs0JvHIGAlOi215IV6e6BMsmboo_HWpW4b3WjiXcc01a2eNtZ7zMaQUsT-HwG0m5rqpqY6Dh3vSlOFZw9467LJJeUp-uFR16u9a5NyiPcrFLQKivpurzpfehzTf79wSHPtbta3rkh_fROX7sE_cPq-5g |
| CODEN | OPREAI |
| CitedBy_id | crossref_primary_10_1016_S0305_0548_98_80006_3 crossref_primary_10_1080_10170669_2000_10432705 crossref_primary_10_1080_10426910701323714 crossref_primary_10_1111_j_1475_3995_2009_00708_x crossref_primary_10_1177_0954405411421996 crossref_primary_10_1111_j_1475_3995_1998_tb00119_x crossref_primary_10_1016_S0167_6377_03_00002_6 crossref_primary_10_1007_s10479_008_0457_4 crossref_primary_10_1016_j_mcm_2011_04_003 crossref_primary_10_1111_j_1475_3995_2000_tb00194_x crossref_primary_10_1080_10170660509509315 crossref_primary_10_1590_S0103_65132013005000023 crossref_primary_10_1016_S0377_2217_02_00129_7 crossref_primary_10_1016_j_ejor_2015_04_044 crossref_primary_10_1287_ijoc_1100_0394 crossref_primary_10_1111_itor_12687 crossref_primary_10_1016_j_ijpe_2013_04_031 crossref_primary_10_1016_j_cie_2009_03_006 crossref_primary_10_1016_S0360_8352_96_00215_X crossref_primary_10_1016_S0305_0548_00_00095_2 crossref_primary_10_1080_00207543_2010_493535 crossref_primary_10_1016_j_cor_2005_05_025 crossref_primary_10_1080_00207543_2012_693965 crossref_primary_10_1109_3468_477872 crossref_primary_10_1016_j_ejor_2004_10_020 crossref_primary_10_1016_S0305_0548_96_00095_0 crossref_primary_10_3390_ijms19113398 crossref_primary_10_1590_S0103_65132007000100003 crossref_primary_10_1016_j_ejor_2014_10_004 crossref_primary_10_1590_S0104_530X2002000100007 crossref_primary_10_1016_j_ejor_2011_11_002 crossref_primary_10_1080_0305215X_2010_522708 crossref_primary_10_1111_j_1475_3995_2009_00701_x crossref_primary_10_1016_j_cie_2011_12_012 crossref_primary_10_1016_j_cor_2006_02_029 crossref_primary_10_1287_ijoc_2016_0708 crossref_primary_10_1007_s10589_007_9103_3 crossref_primary_10_1080_03052150601107984 crossref_primary_10_1007_s10100_018_0551_x crossref_primary_10_1016_j_cor_2012_03_001 crossref_primary_10_1243_09544054JEM268 crossref_primary_10_1080_01605682_2020_1813640 crossref_primary_10_1016_j_ejor_2020_06_050 crossref_primary_10_1016_j_ijpe_2013_03_011 crossref_primary_10_1016_j_cor_2010_01_017 crossref_primary_10_1111_itor_13358 crossref_primary_10_1109_TKDE_2011_72 crossref_primary_10_1016_0004_3702_95_00094_1 crossref_primary_10_1111_itor_12703 crossref_primary_10_1016_S0377_2217_96_00060_4 crossref_primary_10_1016_0377_2217_94_90197_X crossref_primary_10_1016_S0305_0548_98_00008_2 crossref_primary_10_1287_ijoc_1110_0478 crossref_primary_10_1007_s10589_007_9081_5 |
| ContentType | Journal Article |
| Copyright | Copyright 1993 The Operations Research Society of America 1994 INIST-CNRS Copyright Institute for Operations Research and the Management Sciences Jul/Aug 1993 |
| Copyright_xml | – notice: Copyright 1993 The Operations Research Society of America – notice: 1994 INIST-CNRS – notice: Copyright Institute for Operations Research and the Management Sciences Jul/Aug 1993 |
| DBID | AAYXX CITATION IQODW HJHVS IBDFT K30 PAAUG PAWHS PAWZZ PAXOH PBHAV PBQSW PBYQZ PCIWU PCMID PCZJX PDGRG PDWWI PETMR PFVGT PGXDX PIHIL PISVA PJCTQ PJTMS PLCHJ PMHAD PNQDJ POUND PPLAD PQAPC PQCAN PQCMW PQEME PQHKH PQMID PQNCT PQNET PQSCT PQSET PSVJG PVMQY PZGFC 3V. 7WY 7WZ 7X7 7XB 87Z 88E 88F 8AL 8AO 8FE 8FG 8FI 8FJ 8FK 8FL 8G5 ABJCF ABUWG AFKRA ARAPS AZQEC BENPR BEZIV BGLVJ CCPQU DWQXO FRNLG FYUFA F~G GHDGH GNUQQ GUQSH HCIFZ JQ2 K60 K6~ K7- K9. L.- L6V M0C M0N M0S M1P M1Q M2O M7S MBDVC P5Z P62 PHGZM PHGZT PJZUB PKEHL PPXIY PQBIZ PQBZA PQEST PQGLB PQQKQ PQUKI PRINS PTHSS Q9U 7SC 8FD L7M L~C L~D |
| DOI | 10.1287/opre.41.4.768 |
| DatabaseName | CrossRef Pascal-Francis Periodicals Index Online Segment 19 Periodicals Index Online Segment 27 Periodicals Index Online Primary Sources Access—Foundation Edition (Plan E) - West Primary Sources Access (Plan D) - International Primary Sources Access & Build (Plan A) - MEA Primary Sources Access—Foundation Edition (Plan E) - Midwest Primary Sources Access—Foundation Edition (Plan E) - Northeast Primary Sources Access (Plan D) - Southeast Primary Sources Access (Plan D) - North Central Primary Sources Access—Foundation Edition (Plan E) - Southeast Primary Sources Access (Plan D) - South Central Primary Sources Access & Build (Plan A) - UK / I Primary Sources Access (Plan D) - Canada Primary Sources Access (Plan D) - EMEALA Primary Sources Access—Foundation Edition (Plan E) - North Central Primary Sources Access—Foundation Edition (Plan E) - South Central Primary Sources Access & Build (Plan A) - International Primary Sources Access—Foundation Edition (Plan E) - International Primary Sources Access (Plan D) - West Periodicals Index Online Segments 1-50 Primary Sources Access (Plan D) - APAC Primary Sources Access (Plan D) - Midwest Primary Sources Access (Plan D) - MEA Primary Sources Access—Foundation Edition (Plan E) - Canada Primary Sources Access—Foundation Edition (Plan E) - UK / I Primary Sources Access—Foundation Edition (Plan E) - EMEALA Primary Sources Access & Build (Plan A) - APAC Primary Sources Access & Build (Plan A) - Canada Primary Sources Access & Build (Plan A) - West Primary Sources Access & Build (Plan A) - EMEALA Primary Sources Access (Plan D) - Northeast Primary Sources Access & Build (Plan A) - Midwest Primary Sources Access & Build (Plan A) - North Central Primary Sources Access & Build (Plan A) - Northeast Primary Sources Access & Build (Plan A) - South Central Primary Sources Access & Build (Plan A) - Southeast Primary Sources Access (Plan D) - UK / I Primary Sources Access—Foundation Edition (Plan E) - APAC Primary Sources Access—Foundation Edition (Plan E) - MEA ProQuest Central (Corporate) ABI/INFORM Collection ABI/INFORM Global (PDF only) Health & Medical Collection ProQuest Central (purchase pre-March 2016) ABI/INFORM Collection Medical Database (Alumni Edition) Military Database (Alumni Edition) Computing Database (Alumni Edition) ProQuest Pharma Collection ProQuest SciTech Collection ProQuest Technology Collection Hospital Premium Collection Hospital Premium Collection (Alumni Edition) ProQuest Central (Alumni) (purchase pre-March 2016) ABI/INFORM Collection (Alumni) ProQuest Research Library Materials Science & Engineering Collection ProQuest Central (Alumni) ProQuest Central UK/Ireland Advanced Technologies & Aerospace Collection ProQuest Central Essentials Proquest Central Business Premium Collection Technology Collection ProQuest One ProQuest Central Business Premium Collection (Alumni) Health Research Premium Collection ABI/INFORM Global (Corporate) Health Research Premium Collection (Alumni) ProQuest Central Student ProQuest Research Library SciTech Premium Collection ProQuest Computer Science Collection ProQuest Business Collection (Alumni Edition) ProQuest Business Collection Computer Science Database ProQuest Health & Medical Complete (Alumni) ABI/INFORM Professional Advanced ProQuest Engineering Collection ABI/INFORM Global Computing Database ProQuest Health & Medical Collection Medical Database Military Database Research Library Engineering Database Research Library (Corporate) Advanced Technologies & Aerospace Database ProQuest Advanced Technologies & Aerospace Collection ProQuest Central Premium ProQuest One Academic (New) ProQuest Health & Medical Research Collection ProQuest One Academic Middle East (New) ProQuest One Health & Nursing ProQuest One Business ProQuest One Business (Alumni) ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Applied & Life Sciences ProQuest One Academic ProQuest One Academic UKI Edition ProQuest Central China Engineering Collection ProQuest Central Basic Computer and Information Systems Abstracts Technology Research Database Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional |
| DatabaseTitle | CrossRef Periodicals Index Online Segments 1-50 Periodicals Index Online Segment 27 Periodicals Index Online Segment 19 Periodicals Index Online ProQuest Business Collection (Alumni Edition) Research Library Prep Computer Science Database ProQuest Central Student ProQuest Advanced Technologies & Aerospace Collection ProQuest Central Essentials ProQuest Computer Science Collection SciTech Premium Collection ProQuest Military Collection ProQuest Central China ABI/INFORM Complete ProQuest One Applied & Life Sciences Health Research Premium Collection Health & Medical Research Collection ProQuest Central (New) ProQuest Medical Library (Alumni) Engineering Collection Advanced Technologies & Aerospace Collection Business Premium Collection ABI/INFORM Global Engineering Database ProQuest One Academic Eastern Edition ProQuest Hospital Collection ProQuest Technology Collection Health Research Premium Collection (Alumni) ProQuest Business Collection ProQuest Hospital Collection (Alumni) ProQuest Health & Medical Complete ProQuest One Academic UKI Edition ProQuest One Academic ProQuest One Academic (New) ABI/INFORM Global (Corporate) ProQuest One Business Technology Collection ProQuest One Academic Middle East (New) ProQuest Health & Medical Complete (Alumni) ProQuest Central (Alumni Edition) ProQuest One Community College ProQuest One Health & Nursing Research Library (Alumni Edition) ProQuest Pharma Collection ProQuest Central ABI/INFORM Professional Advanced ProQuest Health & Medical Research Collection ProQuest Engineering Collection Health and Medicine Complete (Alumni Edition) ProQuest Central Korea ProQuest Research Library ABI/INFORM Complete (Alumni Edition) ProQuest Computing ABI/INFORM Global (Alumni Edition) ProQuest Central Basic ProQuest Computing (Alumni Edition) ProQuest Military Collection (Alumni Edition) ProQuest SciTech Collection Advanced Technologies & Aerospace Database ProQuest Medical Library Materials Science & Engineering Collection ProQuest One Business (Alumni) ProQuest Central (Alumni) Business Premium Collection (Alumni) Computer and Information Systems Abstracts Technology Research Database Computer and Information Systems Abstracts – Academic Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Professional |
| DatabaseTitleList | ProQuest Business Collection (Alumni Edition) Computer and Information Systems Abstracts CrossRef |
| Database_xml | – sequence: 1 dbid: 8FG name: ProQuest Technology Collection url: https://search.proquest.com/technologycollection1 sourceTypes: Aggregation Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Engineering Sciences (General) Computer Science Business Applied Sciences |
| EISSN | 1526-5463 |
| EndPage | 776 |
| ExternalDocumentID | 704165 3808987 10_1287_opre_41_4_768 171971 opre.41.4.768 opres_41_4_768 |
| Genre | Research Article |
| GroupedDBID | 02 08R 123 1OL 29N 2AX 3V. 4.4 7WY 7X7 85S 88E 8AL 8AO 8FE 8FG 8FI 8FJ 8FL 8G5 8V8 AABCJ ABBHK ABDEX ABEFU ABJCF ABPPZ ABSIS ABUWG ABWPA ACDCL ACHQT ACIWK ACNCT ACVYA ADBBV ADGDI ADNFJ AENEX AEUPB AFKRA AJPNJ AKVCP ALMA_UNASSIGNED_HOLDINGS AQNXB AQSKT ARAPS AZQEC B-7 BBAFP BENPR BEZIV BGLVJ BPHCQ BVXVI CBXGM CCKSF CS3 CWXUR CYVLN DWQXO DZ EBA EBE EBO EBR EBS EBU ECR EHE EJD EMI EMK EPL F20 F5P FRNLG FYUFA G8K GENNL GNUQQ GROUPED_ABI_INFORM_COMPLETE GROUPED_ABI_INFORM_RESEARCH GUPYA GUQSH HCIFZ HGD HVGLF IAO ICJ IEA IGG IOF JAV JBC JPL JSODD JST K6 K60 K6V K7- L6V M0C M0N M1P M1Q M2O M7S MBDVC MV1 N95 P2P P62 PQEST PQQKQ PQUKI PRG PROAC PSQYO PTHSS QVA RNS RPU SA0 TAE TH9 TN5 U5U VQA WH7 X XFK XHC XJT XXP Y99 YHZ YNT YZZ ZCG ZY4 1AW 92 ACUWV AETEA AFFNX FH7 H~9 ITC LI NIEAY XI7 -DZ -~X 18M AAAZS AAWTO AAXLS AAYOK ABAWQ ABDPE ABKVW ABLWH ABXSQ ABYYQ ACGFO ACHJO ACXJH ADEPB ADMHG ADULT AEGXH AFAIT AFTQD AGKTX AHAJD AHQJS AIAGR ALIPV APTMU ASMEE CCPQU HMCUK IPSME JAAYA JBMMH JBZCM JENOY JHFFW JKQEH JLEZI JLXEF JPPEU K1G K6~ PHGZM PHGZT PQBIZ PQBZA UKHRP XOL XSW YYP ~02 AAYXX ACSVP ADMHC ADNWM AEMOZ BAAKF CITATION HF~ ~92 ABTAH IQODW HJHVS IBDFT K30 PAAUG PAWHS PAWZZ PAXOH PBHAV PBQSW PBYQZ PCIWU PCMID PCZJX PDGRG PDWWI PETMR PFVGT PGXDX PIHIL PISVA PJCTQ PJTMS PJZUB PLCHJ PMHAD PNQDJ POUND PPLAD PPXIY PQAPC PQCAN PQCMW PQEME PQGLB PQHKH PQMID PQNCT PQNET PQSCT PQSET PSVJG PVMQY PZGFC 7XB 8FK JQ2 K9. L.- PKEHL PRINS Q9U 7SC 8FD L7M L~C L~D PUEGO |
| ID | FETCH-LOGICAL-c353t-8f10ec8df4a3e1c2ceb1a049513f8745c14296fa53c791eee727e4eb5f165eb23 |
| IEDL.DBID | 8FG |
| ISSN | 0030-364X |
| IngestDate | Fri Sep 05 11:58:28 EDT 2025 Fri Jul 25 11:10:53 EDT 2025 Fri Jul 25 03:11:24 EDT 2025 Wed Apr 02 08:12:04 EDT 2025 Thu Apr 24 23:07:31 EDT 2025 Tue Jul 01 00:21:45 EDT 2025 Thu Jun 19 15:56:13 EDT 2025 Tue Jan 05 23:28:36 EST 2021 Fri Jan 15 03:35:24 EST 2021 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 4 |
| Keywords | Cutting Experimental result Constraint Combinatorial problem Trim loss problem Two dimensional model Search algorithm |
| Language | English |
| License | CC BY 4.0 |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c353t-8f10ec8df4a3e1c2ceb1a049513f8745c14296fa53c791eee727e4eb5f165eb23 |
| Notes | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-1 content type line 23 |
| PQID | 219170186 |
| PQPubID | 1818780 |
| PageCount | 9 |
| ParticipantIDs | informs_primary_10_1287_opre_41_4_768 jstor_primary_171971 crossref_primary_10_1287_opre_41_4_768 pascalfrancis_primary_3808987 highwire_informs_opres_41_4_768 crossref_citationtrail_10_1287_opre_41_4_768 proquest_journals_219170186 proquest_journals_1303086864 proquest_miscellaneous_25942677 |
| ProviderPackageCode | Y99 RPU NIEAY CITATION AAYXX |
| PublicationCentury | 1900 |
| PublicationDate | 19930701 |
| PublicationDateYYYYMMDD | 1993-07-01 |
| PublicationDate_xml | – month: 07 year: 1993 text: 19930701 day: 01 |
| PublicationDecade | 1990 |
| PublicationPlace | Linthicum, MD |
| PublicationPlace_xml | – name: Linthicum, MD – name: Baltimore, Md – name: Linthicum |
| PublicationTitle | Operations research |
| PublicationYear | 1993 |
| Publisher | INFORMS Operations Research Society of America Institute for Operations Research and the Management Sciences |
| Publisher_xml | – name: INFORMS – name: Operations Research Society of America – name: Institute for Operations Research and the Management Sciences |
| SSID | ssj0009565 |
| Score | 1.695324 |
| Snippet | Best-first search is a widely used problem solving technique in the field of artificial intelligence. The method has useful applications in operations research... Best-first search is a widely used problem-solving technique in the field of artificial intelligence. The method has useful applications in operations research... |
| SourceID | proquest pascalfrancis crossref jstor informs highwire |
| SourceType | Aggregation Database Index Database Enrichment Source Publisher |
| StartPage | 768 |
| SubjectTerms | Algorithms Applied sciences Artificial intelligence artificial intelligence: search methods computers/computer science cutting stock/trim: rectangular stock sheets Dynamic programming Exact sciences and technology Experimental results Flows in networks. Combinatorial problems Heuristics Integers Mathematical models Maximum value Operational research and scientific management Operational research. Management science Operations research Optimal solutions Problem solving production/scheduling Rectangles Recursion |
| Title | Best-First Search Methods for Constrained Two-Dimensional Cutting Stock Problems |
| URI | http://or.journal.informs.org/cgi/content/abstract/41/4/768 https://www.jstor.org/stable/171971 https://www.proquest.com/docview/1303086864 https://www.proquest.com/docview/219170186 https://www.proquest.com/docview/25942677 |
| Volume | 41 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwhV3fb9MwED6xTULwAKwDEbYVPwACiXR1_bNPiKGVCYlpQkzqW-Q4toRA7SCt-Pe5S-xSNAGv8eWHc_b5Lv7yfQDPZJi4QAAH4YUppW5E6WQTS6W8b2ouatf9x_3xQp9fyQ9zNU_YnDbBKnNM7AJ1s_T0jfxkQoXFmFv95vp7SaJRtLmaFDR2YI_jQkPD3M7eb3Hu6l7AQGCo0XKeKDaxRjghhZGR5CM5MkSyur0kZZrg7vcmShzbDFUk3KRr8dXFXvPiRvju1qTZA7iXkkn2tvf-PtwKiwHczlj2AdzPmg0sTeEB3N0iIBzAfjrespeJf_rVAVye4q3K-AXzQtZPBNbrTLcMH5R5yihJWCI0bPVzWTakD9BzezC_7mDUDPvhv7IkVtM-hKvZ2ed352USXii9UGJV2sjHwdsmSicC9xOPAd1hKaG4iESP7zmuYjo6JbyZ8hACJkFBhlpFrhWW6uIR7C6Wi_AYGOfOSy1qr3Qjg_VElxdroQNmEk6LSQGv87uvfGIlpz58q6g6QVdV5KpK8kpW6KoCXmzMr3s6jr8ZPs2OrJIbO4N2y-J5bvjPlQ467_-2MnxqeAHHfwyGTbOwYzu1poCjPDiqFBZa2jsUWENaLQs4vNm8GeP49JtWnO60h-MWYblGEzXFnMqYJ_88_xDu9MBMghUfwe7qxzocY_K0qoewY-Zm2E2UIeydnl1cfvoFY00cAw |
| linkProvider | ProQuest |
| linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1Lb9QwEB6VrcTjAHQLIrSlPlAEUrNdx49kDwhRaLWl7apCrbS34DiOhEC7heyq4kfxH5lJ7GVRBZx6jSfPzx7PxOPvA3guXWIcFTgIK9JY6lLERpZVrJS1ZcFFYZp93KcjPbyQH8ZqvAI_w14YKqsMPrFx1OXU0j_yvYQSiz7P9JvLbzGJRtHialDQaHvFsftxhRlb_froPcK7kySHB-fvhrEXFYitUGIWZxXvO5uVlTTCcZtYdFYGw2TFRUXU75ajh9aVUcKmA-6cwwneSVeoimuFaajA696CVUkbWjuwun8wOvu4xPKrW8kEgc5Ny7En9cSsZI80TXqS92QvJVrX5UkwEBM3G6ooVK1DcSRVapoawapalY1rE0YzCx4-hPs-fGVv2_62Bitu0oXboXq-Cw-CSgTzTqML95YoD7uw5o_X7KVnvH61Dmf7eKu4-oyRKGs_MmuVrWuGD8osxbAkZeFKNruaxiUpErRsIszOm8Jthu9hvzAvj1M_gosbQeUxdCbTiXsCjHNjpRaFVbqULrNE0FcVQjuMXYwWSQS74dvn1vOg0zt8zSkfQqhygiqXPJc5QhXBi4X5ZUsA8jfD7QBk7mFsDOoli53Q8J8rrTfo_7ZK-SDlEWz90RkWzSLrZ4MsjWAzdI7cO6KaVisFZq2ZlhFsXG9ejCp8-kUrOhhaNTITN52jiRpgFJemT_95_jbcGZ6fnuQnR6PjDbjbloVSUfMmdGbf524LQ7dZ8cwPGAafbnqM_gJaUlhd |
| linkToPdf | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1Nb9NAEB2VIlVwAJqCMG3pHigCCSdZ75dzQAgoUUuh6oFKubn2eldCoKTgRBU_jX_HjL0bgirg1Gt24th-O7Mz2dn3AJ5Il5WOGhyEFSaVuhZpKWufKmVtXXFRle057o8n-vBMvp-oyRr8jGdhqK0yxsQ2UNczS_-RDzIqLIY81wMfuiJOD8avLr6lJCBFG61RTaObIcfuxyVWb83LowOEej_Lxu8-vT1Mg8BAaoUS8zT3fOhsXntZCsdtZjFwlZgyKy480cBbjtFa-1IJa0bcOYeLvZOuUp5rhSWpwOvegJtGYFKFrmQmZoXvV3fiCQLDnJaTQO-J9cmA1E36kvdl3xDB6-pyGCmK26NVlLQ2sU2SejbLBmHznd7GlaWjXQ_H9-BOSGTZ627mbcKam_ZgI_bR9-Bu1ItgIXz04PYK-WEPNsPnDXsWuK-fb8HpG_yp1H_GnJR1r5h1GtcNwxtllrJZErVwNZtfztKatAk6XhFmF20LN8PnsF9YEMpp7sPZtWDyANans6l7CIzz0kotKqt0LV1uiarPV0I7zGJKLbIEXsR3X9jAiE7P8LWgygihKgiqQvJCFghVAk-X5hcdFcjfDPcikEWAsTVoViz248B_rrTVov_byvCR4Qns_jEZlsMiH-aj3CSwEydHEUJSQ_uWAuvXXMsEtq8OL_0L7345iqGG9o_KqZst0ESNMJ8z5tE_v78HG-iZxYejk-NtuNX1h1J38w6sz78v3C7mcPPqcestDM6v2z1_AViwWyQ |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Best-First+Search+Methods+for+Constrained+Two-Dimensional+Cutting+Stock+Problems&rft.jtitle=Operations+research&rft.date=1993-07-01&rft.pub=INFORMS&rft.issn=0030-364X&rft.eissn=1526-5463&rft.volume=41&rft.issue=4&rft.spage=768&rft.epage=776&rft_id=info:doi/10.1287%2Fopre.41.4.768&rft.externalDocID=opre.41.4.768 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0030-364X&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0030-364X&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0030-364X&client=summon |