A greedy memetic algorithm for a multiobjective dynamic bin packing problem for storing cooling objects

In this paper, a multiobjective dynamic bin packing problem for storing cooling objects is introduced along with a metaheuristic designed to work well in mixed-variable environments. The dynamic bin packing problem is based on cookie production at a bakery, where cookies arrive in batches at a cooli...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Journal of heuristics Jg. 25; H. 1; S. 1 - 45
Hauptverfasser:	Spencer, Kristina Yancey, Tsvetkov, Pavel V., Jarrell, Joshua J.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.02.2019 Springer Nature B.V
Schlagworte:	Artificial Intelligence Benchmarks Boxes Calculus of Variations and Optimal Control; Optimization Cookies Cooling Greedy algorithms Heuristic methods Management Science Mathematics Mathematics and Statistics Multiple objective analysis Operations Research Operations Research/Decision Theory Packing problem Memetic algorithms Multiobjective combinatorial optimization Dynamic bin packing problem Metaheuristics
ISSN:	1381-1231, 1572-9397
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Abstract	In this paper, a multiobjective dynamic bin packing problem for storing cooling objects is introduced along with a metaheuristic designed to work well in mixed-variable environments. The dynamic bin packing problem is based on cookie production at a bakery, where cookies arrive in batches at a cooling rack with limited capacity and are packed into boxes with three competing goals. The first is to minimize the number of boxes used. The second objective is to minimize the average initial heat of each box, and the third is to minimize the maximum time until the boxes can be moved to the storefront. The metaheuristic developed here incorporated greedy heuristics into an adaptive evolutionary framework with partial decomposition into clusters of solutions for the crossover operator. The new metaheuristic was applied to a variety benchmark bin packing problems and to a small and large version of the dynamic bin packing problem. It performed as well as other metaheuristics in the benchmark problems and produced more diverse solutions in the dynamic problems. It performed better overall in the small dynamic problem, but its performance could not be proven to be better or worse in the large dynamic problem.
AbstractList	In this paper, a multiobjective dynamic bin packing problem for storing cooling objects is introduced along with a metaheuristic designed to work well in mixed-variable environments. The dynamic bin packing problem is based on cookie production at a bakery, where cookies arrive in batches at a cooling rack with limited capacity and are packed into boxes with three competing goals. The first is to minimize the number of boxes used. The second objective is to minimize the average initial heat of each box, and the third is to minimize the maximum time until the boxes can be moved to the storefront. The metaheuristic developed here incorporated greedy heuristics into an adaptive evolutionary framework with partial decomposition into clusters of solutions for the crossover operator. The new metaheuristic was applied to a variety benchmark bin packing problems and to a small and large version of the dynamic bin packing problem. It performed as well as other metaheuristics in the benchmark problems and produced more diverse solutions in the dynamic problems. It performed better overall in the small dynamic problem, but its performance could not be proven to be better or worse in the large dynamic problem.
Author	Jarrell, Joshua J. Tsvetkov, Pavel V. Spencer, Kristina Yancey
Author_xml	– sequence: 1 givenname: Kristina Yancey orcidid: 0000-0003-0448-0411 surname: Spencer fullname: Spencer, Kristina Yancey email: kristina.yancey@gmail.com organization: Texas A&M University, 3133 TAMU – sequence: 2 givenname: Pavel V. surname: Tsvetkov fullname: Tsvetkov, Pavel V. organization: Texas A&M University, 3133 TAMU – sequence: 3 givenname: Joshua J. orcidid: 0000-0003-1041-8729 surname: Jarrell fullname: Jarrell, Joshua J. organization: Oak Ridge National Laboratory, Idaho National Laboratory
BookMark	eNp9kMtKxDAUhoMoODP6AO4Crqu5TJtmOQzeYMCNrkOSJjVj29QkI8zbm1JBEHR1TsL_5Zx8S3A6-MEAcIXRDUaI3UaMGCUFwnXBaZ2bE7DAJSP5xNlp7mmNC0woPgfLGPcIIV6XdAHaDWyDMc0R9qY3yWkou9YHl956aH2AEvaHLjmv9kYn92lgcxxkn2PKDXCU-t0NLRyDV52ZgZgyne-0991UZzJegDMru2guv-sKvN7fvWwfi93zw9N2sys0xVUq7NoQWxHJGo15WSskqaTcIrMuMSelqpUhGhOEFK8sU9TWTDLeUEUxllX-0Qpcz-_mnT4OJiax94cw5JGCoGpdMpbhnMJzSgcfYzBWjMH1MhwFRmLyKWafIvsUk08xMewXo12SWc2QgnTdvySZyThOakz42elv6At_SIx3
CitedBy_id	crossref_primary_10_3233_JIFS_201581 crossref_primary_10_1109_TIM_2020_2987636 crossref_primary_10_1007_s11633_023_1468_y crossref_primary_10_1016_j_eswa_2024_123515 crossref_primary_10_1016_j_nucengdes_2019_110479 crossref_primary_10_3390_electronics11020249 crossref_primary_10_1007_s10288_022_00522_4 crossref_primary_10_1007_s10732_024_09537_y crossref_primary_10_1016_j_asoc_2022_109243 crossref_primary_10_1016_j_pnucene_2019_04_009 crossref_primary_10_1080_01605682_2023_2228339
Cites_doi	10.2307/3002019 10.1007/978-3-642-27549-4_58 10.1109/TEVC.2009.2033671 10.1111/j.1365-2621.1978.tb02309.x 10.1016/j.ejor.2007.06.032 10.1109/TCYB.2013.2295886 10.1016/j.ejor.2014.02.059 10.1007/978-3-319-13072-9 10.1007/BFb0056872 10.1016/S0307-904X(00)00026-3 10.1287/opre.42.2.287 10.1016/j.asoc.2013.12.006 10.1201/b16609 10.1109/TEVC.2010.2058117 10.1007/978-3-540-88051-6_2 10.1007/BF01096763 10.1016/j.ejor.2009.05.005 10.1109/TPDS.2015.2393868 10.1016/j.swevo.2011.03.001 10.1007/978-3-642-32964-7_42 10.1109/CEC.2010.5586259 10.1109/4235.996017 10.1109/MCSE.2007.55 10.1109/TEVC.2003.810758
ContentType	Journal Article
Copyright	Springer Science+Business Media, LLC, part of Springer Nature 2018 Journal of Heuristics is a copyright of Springer, (2018). All Rights Reserved.
Copyright_xml	– notice: Springer Science+Business Media, LLC, part of Springer Nature 2018 – notice: Journal of Heuristics is a copyright of Springer, (2018). All Rights Reserved.
DBID	AAYXX CITATION 3V. 7WY 7WZ 7XB 87Z 8AL 8FE 8FG 8FK 8FL ABUWG AFKRA ARAPS AZQEC BENPR BEZIV BGLVJ CCPQU DWQXO FRNLG F~G GNUQQ HCIFZ JQ2 K60 K6~ K7- L.- M0C M0N P5Z P62 PHGZM PHGZT PKEHL PQBIZ PQBZA PQEST PQGLB PQQKQ PQUKI PYYUZ Q9U
DOI	10.1007/s10732-018-9382-0
DatabaseName	CrossRef ProQuest Central (Corporate) ABI/INFORM Collection ABI/INFORM Global (PDF only) ProQuest Central (purchase pre-March 2016) ABI/INFORM Collection Computing Database (Alumni Edition) ProQuest SciTech Collection ProQuest Technology Collection ProQuest Central (Alumni) (purchase pre-March 2016) ABI/INFORM Collection (Alumni) ProQuest Central (Alumni) ProQuest Central UK/Ireland Advanced Technologies & Computer Science Collection ProQuest Central Essentials - QC ProQuest Central Business Premium Collection Technology Collection ProQuest One ProQuest Central Korea Business Premium Collection (Alumni) ABI/INFORM Global (Corporate) ProQuest Central Student SciTech Premium Collection ProQuest Computer Science Collection ProQuest Business Collection (Alumni Edition) ProQuest Business Collection Computer Science Database ABI/INFORM Professional Advanced ABI/INFORM Global Computing Database Advanced Technologies & Aerospace Database ProQuest Advanced Technologies & Aerospace Collection ProQuest Central Premium ProQuest One Academic (New) ProQuest One Academic Middle East (New) ProQuest One Business ProQuest One Business (Alumni) ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Applied & Life Sciences ProQuest One Academic (retired) ProQuest One Academic UKI Edition ABI/INFORM Collection China ProQuest Central Basic
DatabaseTitle	CrossRef ABI/INFORM Global (Corporate) ProQuest Business Collection (Alumni Edition) ProQuest One Business Computer Science Database ProQuest Central Student Technology Collection ProQuest One Academic Middle East (New) ProQuest Advanced Technologies & Aerospace Collection ProQuest Central Essentials ProQuest Computer Science Collection ProQuest Central (Alumni Edition) SciTech Premium Collection ProQuest One Community College ABI/INFORM Complete ProQuest Central ABI/INFORM Professional Advanced ProQuest One Applied & Life Sciences ProQuest Central Korea ProQuest Central (New) ABI/INFORM Complete (Alumni Edition) Advanced Technologies & Aerospace Collection Business Premium Collection ABI/INFORM Global ProQuest Computing ABI/INFORM Global (Alumni Edition) ProQuest Central Basic ProQuest Computing (Alumni Edition) ProQuest One Academic Eastern Edition ABI/INFORM China ProQuest Technology Collection ProQuest SciTech Collection ProQuest Business Collection Advanced Technologies & Aerospace Database ProQuest One Academic UKI Edition ProQuest One Business (Alumni) ProQuest One Academic ProQuest Central (Alumni) ProQuest One Academic (New) Business Premium Collection (Alumni)
DatabaseTitleList	ABI/INFORM Global (Corporate)
Database_xml	– sequence: 1 dbid: BENPR name: ProQuest Central url: https://www.proquest.com/central sourceTypes: Aggregation Database
DeliveryMethod	fulltext_linktorsrc
Discipline	Engineering Mathematics Computer Science
EISSN	1572-9397
EndPage	45
ExternalDocumentID	10_1007_s10732_018_9382_0
GrantInformation_xml	– fundername: US Department of Energy, Office of Nuclear Ene grantid: DE-AC05-00OR22725
GroupedDBID	-52 -5D -5G -BR -EM -~C .4S .86 .DC .VR 06D 0R~ 0VY 1N0 203 29K 2J2 2JN 2JY 2KG 2KM 2LR 2~H 30V 4.4 406 408 409 40D 40E 5GY 5VS 67Z 6NX 7WY 8FE 8FG 8FL 8TC 8UJ 95- 95. 95~ 96X AAAVM AABHQ AACDK AAHNG AAIAL AAJBT AAJKR AANZL AARTL AASML AATNV AATVU AAUYE AAWCG AAYIU AAYQN AAYZH ABAKF ABBBX ABBXA ABDZT ABECU ABFTV ABHLI ABHQN ABJNI ABJOX ABKCH ABKTR ABMNI ABMQK ABNWP ABQBU ABSXP ABTEG ABTHY ABTKH ABTMW ABUWG ABWNU ABXPI ACAOD ACDTI ACGFS ACHSB ACHXU ACKNC ACMDZ ACMLO ACOKC ACOMO ACPIV ACZOJ ADHHG ADHIR ADIMF ADINQ ADKNI ADKPE ADMLS ADRFC ADTPH ADURQ ADYFF ADZKW AEFQL AEGAL AEGNC AEJHL AEJRE AEMSY AENEX AEOHA AEPYU AESKC AETLH AEVLU AEXYK AFBBN AFKRA AFLOW AFQWF AFWTZ AFZKB AGAYW AGDGC AGJBK AGMZJ AGQEE AGQMX AGRTI AGWIL AGWZB AGYKE AHAVH AHBYD AHKAY AHSBF AHYZX AIAKS AIGIU AIIXL AILAN AITGF AJRNO AJZVZ ALMA_UNASSIGNED_HOLDINGS ALWAN AMKLP AMXSW AMYLF AMYQR AOCGG ARAPS ARCSS ARMRJ ASPBG AVWKF AXYYD AYJHY AZFZN AZQEC B-. BA0 BAPOH BDATZ BENPR BEZIV BGLVJ BGNMA BPHCQ BSONS CCPQU CS3 CSCUP D-I DDRTE DL5 DNIVK DPUIP DU5 DWQXO EBLON EBS EDO EIOEI EJD ESBYG FEDTE FERAY FFXSO FIGPU FINBP FNLPD FRNLG FRRFC FSGXE FWDCC GGCAI GGRSB GJIRD GNUQQ GNWQR GQ6 GQ7 GQ8 GROUPED_ABI_INFORM_COMPLETE GROUPED_ABI_INFORM_RESEARCH GXS HCIFZ HF~ HG5 HG6 HMJXF HQYDN HRMNR HVGLF I-F I09 IHE IJ- IKXTQ ITM IWAJR IXC IZIGR IZQ I~X I~Z J-C J0Z JBSCW JCJTX JZLTJ K60 K6V K6~ K7- KDC KOV LAK LLZTM M0C M0N M4Y MA- NB0 NPVJJ NQJWS NU0 O93 O9G O9I O9J OAM P19 P2P P62 P9O PF0 PQBIZ PQBZA PQQKQ PROAC PT4 PT5 QOK QOS R89 R9I RHV ROL RPX RSV S16 S27 S3B SAP SDH SDM SHX SISQX SJYHP SMT SNE SNPRN SNX SOHCF SOJ SPISZ SRMVM SSLCW STPWE SZN T13 TSG TSK TSV TUC TUS U2A UG4 UOJIU UTJUX UZXMN VC2 VFIZW W23 W48 WK8 YLTOR Z45 Z81 Z83 Z86 Z88 Z8U Z8W Z92 ZMTXR ~EX -Y2 1SB 2.D 28- 2P1 2VQ 5QI AAPKM AARHV AAYTO AAYXX ABBRH ABDBE ABFSG ABQSL ABRTQ ABULA ACBXY ACSTC ADHKG ADKFA AEBTG AEFIE AEKMD AEZWR AFDZB AFEXP AFFHD AFGCZ AFHIU AFOHR AGGDS AGQPQ AHPBZ AHWEU AIXLP AJBLW ATHPR AYFIA BBWZM CAG CITATION COF H13 HZ~ KOW N2Q NDZJH O9- OVD PHGZM PHGZT PQGLB Q2X R4E RNI RZC RZD RZK S1Z S26 S28 SCLPG SDD T16 TEORI ZWQNP 3V. 7XB 8AL 8FK JQ2 L.- PKEHL PQEST PQUKI Q9U
ID	FETCH-LOGICAL-c316t-f4e2f62a7dc1958b0a3a39f0e451925b8be2c1200b96f7b3f87a79d3b311a6853
IEDL.DBID	RSV
ISICitedReferencesCount	15
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000458048900001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	1381-1231
IngestDate	Tue Nov 04 23:00:00 EST 2025 Sat Nov 29 06:01:08 EST 2025 Tue Nov 18 21:31:32 EST 2025 Fri Feb 21 02:36:39 EST 2025
IsPeerReviewed	true
IsScholarly	true
Issue	1
Keywords	Memetic algorithms Multiobjective combinatorial optimization Dynamic bin packing problem Metaheuristics
Language	English
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c316t-f4e2f62a7dc1958b0a3a39f0e451925b8be2c1200b96f7b3f87a79d3b311a6853
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14
ORCID	0000-0003-0448-0411 0000-0003-1041-8729
PQID	2064577200
PQPubID	26068
PageCount	45
ParticipantIDs	proquest_journals_2064577200 crossref_primary_10_1007_s10732_018_9382_0 crossref_citationtrail_10_1007_s10732_018_9382_0 springer_journals_10_1007_s10732_018_9382_0
PublicationCentury	2000
PublicationDate	2019-02-01
PublicationDateYYYYMMDD	2019-02-01
PublicationDate_xml	– month: 02 year: 2019 text: 2019-02-01 day: 01
PublicationDecade	2010
PublicationPlace	New York
PublicationPlace_xml	– name: New York – name: Boston
PublicationTitle	Journal of heuristics
PublicationTitleAbbrev	J Heuristics
PublicationYear	2019
Publisher	Springer US Springer Nature B.V
Publisher_xml	– name: Springer US – name: Springer Nature B.V
References	AnilySBramelJSimchi-LeviDWorst-case analysis of heuristics for the bin packing problem with general cost structuresOper. Res.199442228729810.1287/opre.42.2.2870805.90092 Grunert da Fonseca, V., Fonseca, C.M., Hall, A.O.: Inferential performance assessment of stochastic optimisers and the attainment function. In: Zitzler, E., Thiele, L., Deb, K., Coello Coello, C.A. (eds.) Evolutionary Multi-Criterion Optimization: First International Conference, EMO 2001, Zurich, Switzerland, March 7–9, 2001. Proceedings, pp. 213–225. Springer, Berlin (2001) IshibuchiHHitotsuyanagiYTsukamotoNNojimaYImplementation of multiobjective memetic algorithms for combinatorial optimization problems: a knapsack problem case studyStud. Comput. Intell.200917127491188.68120 SilvaEOliveiraJFWäscherG2DCPackGen: a problem generator for two-dimensional rectangular cutting and packing problemsEur. J. Oper. Res.2014237846856319892610.1016/j.ejor.2014.02.0591338.90355 GohCKTanKCLiuDSChiamSA competitive and cooperative co-evolutionary approach to multi-objective particle swarm optimization algorithm designEur. J. Oper. Res.2010202425410.1016/j.ejor.2009.05.0051175.90352 Ochoa, G., Walker, J., Hyde, M., Curtois, T.: Adaptive evolutionary algorithms and extensions to the hyflex hyper-heuristic framework. In: Coello, C.A.C., Cutello, V., Deb, K., Forrest, S., Nicosia, G., Pavone, M. (eds.) Parallel Problem Solving from Nature—PPSN XII: 12th International Conference, Taormina, Italy, September 1–5, 2012, Proceedings, Part II, Springer, Berlin, pp. 418–427 (2012) Lee, K.D., Hubbard, S.: Data Structures and Algorithms with Python. Undergraduate Topics in Computer Science, Springer International Publishing Switzerland (2015) AdraSFFleminPJDiversity management in evolutionary many-objective optimizationIEEE Trans. Evol. Comput.201115218319510.1109/TEVC.2010.2058117 CengelYAHeat Transfer: A Practical Approach20022New YorkMcgraw-HillISBN-10: 0072458933 LiYTangXCaiWDyanmic bin packing for on-demand cloud resource allocationIEEE Trans. Parallel Distrib. Syst.201627115717010.1109/TPDS.2015.2393868 KulackiFAKennedySCMeasurement of the thermophysical properties of common cookie coughJ. Food Sci.19784338038410.1111/j.1365-2621.1978.tb02309.x Nicoarǎ, E.S.: Performance measures for multi-objective optimization algorithms. Buletinul Universitǎţii Petrol–Gaze din Ploieşti, Seria Matematicǎ-Informaticǎ-Fizicǎ 59(1), 19–28 (2007) Lara, O.D., Labrador, M.A.: A multiobjective ant colony-based optimization algorithm for the bin packing problem with load balancing. In: 2010 IEEE Congress on Evolutionary Computation (CEC), pp. 1–8. IEEE (2010) ButenkoSPardalosPMNumerical Methods and Optimization: An Introduction2014Boca RatonCRC Press10.1201/b166091288.65001 DahmaniNClautiauxFKrichenSTalbiEGSelf-adaptive metaheuristics for solving a multi-objective 2-dimensional vector packing problemAppl. Soft Comput.20141612413610.1016/j.asoc.2013.12.006 Dartey, C.K., Finley, J.W., Thulin, R.R.: Process for Preparing Chocolate Chip Cookies Containing Low Melting Fat and Product. U.S. Patent No. 4,722,849, Issued Date February 2 (1988) Fonseca, C.M., Guerreiro, A.P., López-Ibáñez, M., Paquete, L.: On the computation of the empirical attainment function. In: Takahashi, R.H., Deb, K., Wanner, E.F., Greco, S. (eds.) Evolutionary Multi-Criterion Optimization: 6th International Conference, EMO 2011, Ouro Preto, Brazil, April 5–8, 2011. Proceedings, pp. 106–120. Springer, Berlin (2011) KeLZhangQBattitiRHybridization of decomposition and local search for multiobjective optimizationIEEE Tran. Cybern.201444101808182010.1109/TCYB.2013.2295886 DebKPratapAAgarwalSMeyarivanTA fast and elitist multiobjective genetic algorithm: NSGA-IIIEEE Trans. Evol. Comput.20026218219710.1109/4235.996017 Zitzler, E., Thiele, L.: Parallel Problem Solving from Nature (PPSN V), Springer, Berlin, Germany, Book Section Multiobjective Optimization Using Evolutionary Algorithms—A Comparative Case Study, pp. 292–301 (1998) Martello, S., Toth, P.: Knapsack Problems: Algorithms and Computer Implementations. Wiley, New York, Chapter 8. Bin-packing problem, pp. 221–245 (1990) SatterthwaiteFAn approximate distribution of estimates of variance componentsBiom. Bull.19462611011410.2307/3002019 HunterJMatplotlib: a 2D graphics environmentComput. Sci. Eng.200793909510.1109/MCSE.2007.55 Chwatal, A.M., Pirkwieser, S.: Solving the two-dimensional bin-packing problem with variable bin sizes by greedy randomized adaptive search procedures and variable neighborhood search. In: International Conference on Computer Aided Systems Theory, pp. 456–463 (2011) Fonseca, C.M., Knowles, J.D., Thiele, L., Zitzler, E.: A tutorial on the performance assessment of stochastic multiobjective optimizers. In: Evolutionary Multi-Criterion Optimization: First International Conference, EMO 2005, Guanajauto, Mexico (2005) NitinNKarweMVWelti-ChanesJVelez-RuizJFBarbosa-CánovasGVHeat transfer coefficient for model cookies in a turbulent multiple jet impingement systemTransport Phenomena in Food Processing2002Boca RatonCRC Press357376 ZhangQLiuWTsangEVirginasBExpensive multiobjective optimization by MOEA/D with gaussian process modelIEEE Trans. Evol. Comput.201014345647310.1109/TEVC.2009.2033671 FeoTAResendeMGGreedy randomized adaptive search proceduresJ. Global Optim.19956109133132287510.1007/BF010967630822.90110 ZhouAQuBYLiHZhaoSZSuganthanPNZhangQMultiobjective evolutionary algorithms: a survey of the state of the artSwarm Evolut. Comput.201111324910.1016/j.swevo.2011.03.001 Abdi, H.: Encyclopedia of Measurements and Statistics, Thousand Oaks, CA, Chapter, The Bonferroni and Sidak Corrections for Multiple Procedures (2007) LiuDSTanKCHuangSYGohCKHoWKOn solving multiobjective bin packing problems using evolutionary particle swarm optimizationEur. J. Oper. Res.20081902357382241297910.1016/j.ejor.2007.06.0321146.90510 CaoYJJiangLWuQHAn evolutionary programming approach to mixed-variable optimization problemsAppl. Math. Model.20002493194210.1016/S0307-904X(00)00026-31168.90636 SatheMSchenkOBurkhartHSolving Bi-objective Many-Constraint Bin Packing Problems in Automobile Sheet Metal Forming Processes2009BerlinSpringer246260 ZitzlerEThieleLLaumannsMFonsecaCMFonsecaVGdPerformance assessment of multiobjective optimizers: an analysis and reviewIEEE Trans. Evol. Comput.20037211713210.1109/TEVC.2003.810758 9382_CR7 S Anily (9382_CR3) 1994; 42 9382_CR9 J Hunter (9382_CR16) 2007; 9 9382_CR1 M Sathe (9382_CR28) 2009 E Zitzler (9382_CR34) 2003; 7 A Zhou (9382_CR32) 2011; 1 YJ Cao (9382_CR5) 2000; 24 N Nitin (9382_CR26) 2002 TA Feo (9382_CR11) 1995; 6 H Ishibuchi (9382_CR17) 2009; 171 9382_CR20 9382_CR21 9382_CR27 9382_CR24 9382_CR25 Y Li (9382_CR22) 2016; 27 F Satterthwaite (9382_CR29) 1946; 2 YA Cengel (9382_CR6) 2002 L Ke (9382_CR18) 2014; 44 S Butenko (9382_CR4) 2014 FA Kulacki (9382_CR19) 1978; 43 Q Zhang (9382_CR31) 2010; 14 N Dahmani (9382_CR8) 2014; 16 DS Liu (9382_CR23) 2008; 190 CK Goh (9382_CR14) 2010; 202 9382_CR33 9382_CR12 E Silva (9382_CR30) 2014; 237 9382_CR15 K Deb (9382_CR10) 2002; 6 9382_CR13 SF Adra (9382_CR2) 2011; 15
References_xml	– reference: NitinNKarweMVWelti-ChanesJVelez-RuizJFBarbosa-CánovasGVHeat transfer coefficient for model cookies in a turbulent multiple jet impingement systemTransport Phenomena in Food Processing2002Boca RatonCRC Press357376 – reference: Zitzler, E., Thiele, L.: Parallel Problem Solving from Nature (PPSN V), Springer, Berlin, Germany, Book Section Multiobjective Optimization Using Evolutionary Algorithms—A Comparative Case Study, pp. 292–301 (1998) – reference: Fonseca, C.M., Guerreiro, A.P., López-Ibáñez, M., Paquete, L.: On the computation of the empirical attainment function. In: Takahashi, R.H., Deb, K., Wanner, E.F., Greco, S. (eds.) Evolutionary Multi-Criterion Optimization: 6th International Conference, EMO 2011, Ouro Preto, Brazil, April 5–8, 2011. Proceedings, pp. 106–120. Springer, Berlin (2011) – reference: ButenkoSPardalosPMNumerical Methods and Optimization: An Introduction2014Boca RatonCRC Press10.1201/b166091288.65001 – reference: Grunert da Fonseca, V., Fonseca, C.M., Hall, A.O.: Inferential performance assessment of stochastic optimisers and the attainment function. In: Zitzler, E., Thiele, L., Deb, K., Coello Coello, C.A. (eds.) Evolutionary Multi-Criterion Optimization: First International Conference, EMO 2001, Zurich, Switzerland, March 7–9, 2001. Proceedings, pp. 213–225. Springer, Berlin (2001) – reference: ZitzlerEThieleLLaumannsMFonsecaCMFonsecaVGdPerformance assessment of multiobjective optimizers: an analysis and reviewIEEE Trans. Evol. Comput.20037211713210.1109/TEVC.2003.810758 – reference: LiuDSTanKCHuangSYGohCKHoWKOn solving multiobjective bin packing problems using evolutionary particle swarm optimizationEur. J. Oper. Res.20081902357382241297910.1016/j.ejor.2007.06.0321146.90510 – reference: SatheMSchenkOBurkhartHSolving Bi-objective Many-Constraint Bin Packing Problems in Automobile Sheet Metal Forming Processes2009BerlinSpringer246260 – reference: HunterJMatplotlib: a 2D graphics environmentComput. Sci. Eng.200793909510.1109/MCSE.2007.55 – reference: Martello, S., Toth, P.: Knapsack Problems: Algorithms and Computer Implementations. Wiley, New York, Chapter 8. Bin-packing problem, pp. 221–245 (1990) – reference: Abdi, H.: Encyclopedia of Measurements and Statistics, Thousand Oaks, CA, Chapter, The Bonferroni and Sidak Corrections for Multiple Procedures (2007) – reference: IshibuchiHHitotsuyanagiYTsukamotoNNojimaYImplementation of multiobjective memetic algorithms for combinatorial optimization problems: a knapsack problem case studyStud. Comput. Intell.200917127491188.68120 – reference: GohCKTanKCLiuDSChiamSA competitive and cooperative co-evolutionary approach to multi-objective particle swarm optimization algorithm designEur. J. Oper. Res.2010202425410.1016/j.ejor.2009.05.0051175.90352 – reference: SatterthwaiteFAn approximate distribution of estimates of variance componentsBiom. Bull.19462611011410.2307/3002019 – reference: AnilySBramelJSimchi-LeviDWorst-case analysis of heuristics for the bin packing problem with general cost structuresOper. Res.199442228729810.1287/opre.42.2.2870805.90092 – reference: Chwatal, A.M., Pirkwieser, S.: Solving the two-dimensional bin-packing problem with variable bin sizes by greedy randomized adaptive search procedures and variable neighborhood search. In: International Conference on Computer Aided Systems Theory, pp. 456–463 (2011) – reference: Dartey, C.K., Finley, J.W., Thulin, R.R.: Process for Preparing Chocolate Chip Cookies Containing Low Melting Fat and Product. U.S. Patent No. 4,722,849, Issued Date February 2 (1988) – reference: Lara, O.D., Labrador, M.A.: A multiobjective ant colony-based optimization algorithm for the bin packing problem with load balancing. In: 2010 IEEE Congress on Evolutionary Computation (CEC), pp. 1–8. IEEE (2010) – reference: Nicoarǎ, E.S.: Performance measures for multi-objective optimization algorithms. Buletinul Universitǎţii Petrol–Gaze din Ploieşti, Seria Matematicǎ-Informaticǎ-Fizicǎ 59(1), 19–28 (2007) – reference: Lee, K.D., Hubbard, S.: Data Structures and Algorithms with Python. Undergraduate Topics in Computer Science, Springer International Publishing Switzerland (2015) – reference: DebKPratapAAgarwalSMeyarivanTA fast and elitist multiobjective genetic algorithm: NSGA-IIIEEE Trans. Evol. Comput.20026218219710.1109/4235.996017 – reference: KulackiFAKennedySCMeasurement of the thermophysical properties of common cookie coughJ. Food Sci.19784338038410.1111/j.1365-2621.1978.tb02309.x – reference: KeLZhangQBattitiRHybridization of decomposition and local search for multiobjective optimizationIEEE Tran. Cybern.201444101808182010.1109/TCYB.2013.2295886 – reference: AdraSFFleminPJDiversity management in evolutionary many-objective optimizationIEEE Trans. Evol. Comput.201115218319510.1109/TEVC.2010.2058117 – reference: DahmaniNClautiauxFKrichenSTalbiEGSelf-adaptive metaheuristics for solving a multi-objective 2-dimensional vector packing problemAppl. Soft Comput.20141612413610.1016/j.asoc.2013.12.006 – reference: Ochoa, G., Walker, J., Hyde, M., Curtois, T.: Adaptive evolutionary algorithms and extensions to the hyflex hyper-heuristic framework. In: Coello, C.A.C., Cutello, V., Deb, K., Forrest, S., Nicosia, G., Pavone, M. (eds.) Parallel Problem Solving from Nature—PPSN XII: 12th International Conference, Taormina, Italy, September 1–5, 2012, Proceedings, Part II, Springer, Berlin, pp. 418–427 (2012) – reference: CaoYJJiangLWuQHAn evolutionary programming approach to mixed-variable optimization problemsAppl. Math. Model.20002493194210.1016/S0307-904X(00)00026-31168.90636 – reference: FeoTAResendeMGGreedy randomized adaptive search proceduresJ. Global Optim.19956109133132287510.1007/BF010967630822.90110 – reference: CengelYAHeat Transfer: A Practical Approach20022New YorkMcgraw-HillISBN-10: 0072458933 – reference: ZhangQLiuWTsangEVirginasBExpensive multiobjective optimization by MOEA/D with gaussian process modelIEEE Trans. Evol. Comput.201014345647310.1109/TEVC.2009.2033671 – reference: ZhouAQuBYLiHZhaoSZSuganthanPNZhangQMultiobjective evolutionary algorithms: a survey of the state of the artSwarm Evolut. Comput.201111324910.1016/j.swevo.2011.03.001 – reference: Fonseca, C.M., Knowles, J.D., Thiele, L., Zitzler, E.: A tutorial on the performance assessment of stochastic multiobjective optimizers. In: Evolutionary Multi-Criterion Optimization: First International Conference, EMO 2005, Guanajauto, Mexico (2005) – reference: LiYTangXCaiWDyanmic bin packing for on-demand cloud resource allocationIEEE Trans. Parallel Distrib. Syst.201627115717010.1109/TPDS.2015.2393868 – reference: SilvaEOliveiraJFWäscherG2DCPackGen: a problem generator for two-dimensional rectangular cutting and packing problemsEur. J. Oper. Res.2014237846856319892610.1016/j.ejor.2014.02.0591338.90355 – ident: 9382_CR13 – volume: 2 start-page: 110 issue: 6 year: 1946 ident: 9382_CR29 publication-title: Biom. Bull. doi: 10.2307/3002019 – start-page: 357 volume-title: Transport Phenomena in Food Processing year: 2002 ident: 9382_CR26 – volume-title: Heat Transfer: A Practical Approach year: 2002 ident: 9382_CR6 – ident: 9382_CR7 doi: 10.1007/978-3-642-27549-4_58 – volume: 14 start-page: 456 issue: 3 year: 2010 ident: 9382_CR31 publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2009.2033671 – volume: 43 start-page: 380 year: 1978 ident: 9382_CR19 publication-title: J. Food Sci. doi: 10.1111/j.1365-2621.1978.tb02309.x – start-page: 246 volume-title: Solving Bi-objective Many-Constraint Bin Packing Problems in Automobile Sheet Metal Forming Processes year: 2009 ident: 9382_CR28 – volume: 190 start-page: 357 issue: 2 year: 2008 ident: 9382_CR23 publication-title: Eur. J. Oper. Res. doi: 10.1016/j.ejor.2007.06.032 – volume: 44 start-page: 1808 issue: 10 year: 2014 ident: 9382_CR18 publication-title: IEEE Tran. Cybern. doi: 10.1109/TCYB.2013.2295886 – volume: 237 start-page: 846 year: 2014 ident: 9382_CR30 publication-title: Eur. J. Oper. Res. doi: 10.1016/j.ejor.2014.02.059 – ident: 9382_CR15 – ident: 9382_CR21 doi: 10.1007/978-3-319-13072-9 – ident: 9382_CR33 doi: 10.1007/BFb0056872 – ident: 9382_CR24 – volume: 24 start-page: 931 year: 2000 ident: 9382_CR5 publication-title: Appl. Math. Model. doi: 10.1016/S0307-904X(00)00026-3 – volume: 42 start-page: 287 issue: 2 year: 1994 ident: 9382_CR3 publication-title: Oper. Res. doi: 10.1287/opre.42.2.287 – volume: 16 start-page: 124 year: 2014 ident: 9382_CR8 publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2013.12.006 – volume-title: Numerical Methods and Optimization: An Introduction year: 2014 ident: 9382_CR4 doi: 10.1201/b16609 – volume: 15 start-page: 183 issue: 2 year: 2011 ident: 9382_CR2 publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2010.2058117 – volume: 171 start-page: 27 year: 2009 ident: 9382_CR17 publication-title: Stud. Comput. Intell. doi: 10.1007/978-3-540-88051-6_2 – volume: 6 start-page: 109 year: 1995 ident: 9382_CR11 publication-title: J. Global Optim. doi: 10.1007/BF01096763 – volume: 202 start-page: 42 year: 2010 ident: 9382_CR14 publication-title: Eur. J. Oper. Res. doi: 10.1016/j.ejor.2009.05.005 – volume: 27 start-page: 157 issue: 1 year: 2016 ident: 9382_CR22 publication-title: IEEE Trans. Parallel Distrib. Syst. doi: 10.1109/TPDS.2015.2393868 – ident: 9382_CR9 – ident: 9382_CR12 – volume: 1 start-page: 32 issue: 1 year: 2011 ident: 9382_CR32 publication-title: Swarm Evolut. Comput. doi: 10.1016/j.swevo.2011.03.001 – ident: 9382_CR27 doi: 10.1007/978-3-642-32964-7_42 – ident: 9382_CR20 doi: 10.1109/CEC.2010.5586259 – volume: 6 start-page: 182 issue: 2 year: 2002 ident: 9382_CR10 publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/4235.996017 – ident: 9382_CR25 – volume: 9 start-page: 90 issue: 3 year: 2007 ident: 9382_CR16 publication-title: Comput. Sci. Eng. doi: 10.1109/MCSE.2007.55 – volume: 7 start-page: 117 issue: 2 year: 2003 ident: 9382_CR34 publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2003.810758 – ident: 9382_CR1
SSID	ssj0009853
Score	2.2762926
Snippet	In this paper, a multiobjective dynamic bin packing problem for storing cooling objects is introduced along with a metaheuristic designed to work well in...
SourceID	proquest crossref springer
SourceType	Aggregation Database Enrichment Source Index Database Publisher
StartPage	1
SubjectTerms	Artificial Intelligence Benchmarks Boxes Calculus of Variations and Optimal Control; Optimization Cookies Cooling Greedy algorithms Heuristic methods Management Science Mathematics Mathematics and Statistics Multiple objective analysis Operations Research Operations Research/Decision Theory Packing problem
SummonAdditionalLinks	– databaseName: ProQuest Central dbid: BENPR link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV09T8MwED1BywADhQKiUJAHJlAkO27jZEIFFTGgqkKAukW24xRQv2gLv59z4hBAogtrEluOnn2-O5_fAzgLqYiETHzPiDaz2SpcUlJqL1HaEsSJdpqlBp7uRK8XDgZR3yXcFq6ssrCJmaFOptrmyDFID1ptdAUpvZy9eVY1yp6uOgmNdahapjKc59Wrbq9_X9LuhhkPJcN9yUMbzYpzzfzynOC2LAFHx9HNpD93ptLd_HVCmm08N7X_DnkHtp3LSTr5HNmFNTOpQ62QcyBudddh6xs34R4MOwRDcbTBZGzG9qYjkaMh9r58HhN0dIkkWS3iVL3mJpMkubY9wVCbYCBuU_DEydVkDTI6Enymp1YnaEjylot9eLzpPlzfek6VwdOcBUsvbRk_DXwpEm2JahSVXPIopcYS1fhtFSrja4Y_raIgFYqnoZAiSrjijMkA8TiAymQ6MYdAhNBK-TQRzPBWlNBIqcBXoWT4WIbKbwAtEIm1oyy3yhmjuCRbtiDGCGJsQYxpA86_msxyvo5VHzcL4GK3dBdxiVoDLgroy9d_dna0urNj2ERfK8oLvptQWc7fzQls6I_ly2J-6ubtJ5WC87Y priority: 102 providerName: ProQuest
Title	A greedy memetic algorithm for a multiobjective dynamic bin packing problem for storing cooling objects
URI	https://link.springer.com/article/10.1007/s10732-018-9382-0 https://www.proquest.com/docview/2064577200
Volume	25
WOSCitedRecordID	wos000458048900001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText	1
inHoldings	1
isFullTextHit
isPrint
journalDatabaseRights	– providerCode: PRVAVX databaseName: Springer Journals customDbUrl: eissn: 1572-9397 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0009853 issn: 1381-1231 databaseCode: RSV dateStart: 19970101 isFulltext: true titleUrlDefault: https://link.springer.com/search?facet-content-type=%22Journal%22 providerName: Springer Nature
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1ZSwMxEB7U-qAP3uJRSx58UhZyuJvdRxVFUEvxqMfLkmSzVbGtdKu_38ketooK-hLISchkJjPJ5BuA7ZDKSKqEe1b6zN1WIUspZbxEGwcQJ_00vxpon8lmM7y9jVrlP-6s8navniRzST322U0K50aAowlUC9FOr_kObMaZ6JftEdJumENPMjyKPBTLrHrK_G6Iz4fRSMP88iianzXH8_-a5QLMlaol2S_2wiJM2N4SzFdhG0jJxUswO4ZBiLnzD-DWbBk6-wQNcJS8pGu77n8jUc-d_uBx-NAlqN4SRXIPxL5-KgQlSYqI9gQNbILmt7t4J2WQmrxDDkKCZabvogN1SNEzW4Hr46OrwxOvjMXgGcGCoZfuWZ4GXMnEOHgaTZVQIkqpdfA03NehttwwZDkdBanUIg2lklEitGBMBUiSVZjq9Xt2DYiURmtOE8ms2IsSGmkdcB0qhsUq1HwdaEWU2JRA5S5exnM8glh2ixzjIsdukWO6DjsfXV4KlI7fGtcrSsclw2Yxd7h9aGlQrN6tKDuq_nGwjT-13oQZVLiiwuu7DlPDwavdgmnzNnzMBg2YlDd3DagdHDVbF5g7lR6m5_QQ05Z_38j3-Ts6-_HN
linkProvider	Springer Nature
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1LT9wwEB4hWgl6KOWlbkuLD_QCiuTHbpwcKoRoEYhl1QMgbsF2nO1WbHa7u1Dtn-pvZCaPpkUqNw5cE9uRnW8e9oy_AdiJuI61SWXgdUfQaRWKlDEuSK0jgjjdyYqjgcuu7vWiq6v42wL8ru_CUFplrRMLRZ2OHJ2R4yY9bHfQFeR8f_wzoKpRFF2tS2iUsDj181-4ZZt-PvmC__eTlEdfzw-Pg6qqQOCUCGdB1vYyC6XRqSOiFcuNMirOuCeiFdmxkfXSCfyOjcNMW5VF2ug4VVYJYcKIqkSgyn_Rxo0XydUZP2xIfqOC9VKgFQzQIog6ilpe1dOKkiBwLRQ6tfxfO9g4tw_isYWZO1p5bgv0Bl5XDjU7KCVgFRZ8vgYrdbEKVumuNXj1F_PiOvQPWH-ChnvOhn5I9ziZuenjbGbfhwzdeGZYkWk5sj9Kg8DSeW6G2MwOcjY2jgIMrCrGU3QoyFbwmRtRFaQ-K3tON-DiSSa_CYv5KPdvgWntrJU81cKrdpzy2NpQ2sgIfGwiK1vAawQkriJkp7ogN0lDJU2gSRA0CYEm4S3Y_dNlXLKRPNZ4qwZKUimmadKgpAV7NdSa1_8d7N3jg23D0vH5WTfpnvRO38MyepVxmdq-BYuzya3_AC_d3WwwnXwsJIbB9VMj8B4NzE5H
linkToPdf	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1Nb9QwEB1VpUJwoKWAWFqKD3ABRfhjEzsHhCraFVWr1R4AVVyC7ThLUTe77C6g_Wv9dczkg5RK9NYD18R2ZOd5ZmyP3wN4brhOtc1lFHQsaLcKp5S1PsqdJ4I4HRfV1sCnEz0cmtPTdLQGF-1dGEqrbG1iZajzqac9clykJ_0YQ0HOXxdNWsToYPB29j0iBSk6aW3lNGqIHIfVL1y-Ld4cHeC_fiHl4PDDu_dRozAQeSWSZVT0gywSaXXuiXTFcausSgseiHRFxs64IL3Ab7o0KbRThdFWp7lySgibGFKMQPN_S_cTQ-lko_hzR_hrKgZMgR4xQu8g2hPV-tqeVpQQgeOiMMDlf_vELtC9cjZbubzB5v88WFtwrwm02X49M-7DWii3YbMVsWCNTduGu5cYGR_AeJ-N5-jQV2wSJnS_k9nzMfZm-XXCMLxnllUZmFP3rXYULF-VdoLF3FnJZtbTwQNrRHqqChUJCz7zU1JHGrO65uIhfLyRzj-C9XJahsfAtPbOSZ5rEVQ_zXnqXCKdsQIfW-NkD3iLhsw3RO2kF3KedRTTBKAMAZQRgDLeg5d_qsxqlpLrCu-2oMkag7XIOsT04FULu-71Pxt7cn1jz-A2Ai87ORoe78AdDDbTOuN9F9aX8x_hKWz4n8uzxXyvmjwMvtw0AH8Dt6ZXVw
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=A+greedy+memetic+algorithm+for+a+multiobjective+dynamic+bin+packing+problem+for+storing+cooling+objects&rft.jtitle=Journal+of+heuristics&rft.au=Spencer%2C+Kristina+Yancey&rft.au=Tsvetkov%2C+Pavel+V.&rft.au=Jarrell%2C+Joshua+J.&rft.date=2019-02-01&rft.pub=Springer+US&rft.issn=1381-1231&rft.eissn=1572-9397&rft.volume=25&rft.issue=1&rft.spage=1&rft.epage=45&rft_id=info:doi/10.1007%2Fs10732-018-9382-0&rft.externalDocID=10_1007_s10732_018_9382_0
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1381-1231&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1381-1231&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1381-1231&client=summon