An approximate dynamic programming approach for the vehicle routing problem with stochastic demands

This paper examines approximate dynamic programming algorithms for the single-vehicle routing problem with stochastic demands from a dynamic or reoptimization perspective. The methods extend the rollout algorithm by implementing different base sequences (i.e. a priori solutions), look-ahead policies...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	European journal of operational research Ročník 196; číslo 2; s. 509 - 515
Hlavní autori:	Novoa, Clara, Storer, Robert
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Amsterdam Elsevier B.V 16.07.2009 Elsevier Elsevier Sequoia S.A
Edícia:	European Journal of Operational Research
Predmet:	Applied sciences Approximate dynamic programming Dynamic programming Exact sciences and technology Logistics Monte Carlo simulation Operational research and scientific management Operational research. Management science Optimization algorithms Routing Stochastic models Stochastic vehicle routing Studies Transportation Transportation Stochastic vehicle routing Approximate dynamic programming Stochastic vehicle routing Approximate dynamic programming Transportation Monte Carlo method Filtering Vehicle routing problem Routing Modeling Confidence interval Exact solution Computation time Pruning(tree) Cost estimation Dynamic programming
ISSN:	0377-2217, 1872-6860
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Abstract	This paper examines approximate dynamic programming algorithms for the single-vehicle routing problem with stochastic demands from a dynamic or reoptimization perspective. The methods extend the rollout algorithm by implementing different base sequences (i.e. a priori solutions), look-ahead policies, and pruning schemes. The paper also considers computing the cost-to-go with Monte Carlo simulation in addition to direct approaches. The best new method found is a two-step lookahead rollout started with a stochastic base sequence. The routing cost is about 4.8% less than the one-step rollout algorithm started with a deterministic sequence. Results also show that Monte Carlo cost-to-go estimation reduces computation time 65% in large instances with little or no loss in solution quality. Moreover, the paper compares results to the perfect information case from solving exact a posteriori solutions for sampled vehicle routing problems. The confidence interval for the overall mean difference is (3.56%, 4.11%).
AbstractList	This paper examines approximate dynamic programming algorithms for the single-vehicle routing problem with stochastic demands from a dynamic or reoptimization perspective. The methods extend the rollout algorithm by implementing different base sequences (i.e. a priori solutions), look-ahead policies, and pruning schemes. The paper also considers computing the cost-to-go with Monte Carlo simulation in addition to direct approaches. The best new method found is a two-step lookahead rollout started with a stochastic base sequence. The routing cost is about 4.8% less than the one-step rollout algorithm started with a deterministic sequence. Results also show that Monte Carlo cost-to-go estimation reduces computation time 65% in large instances with little or no loss in solution quality. Moreover, the paper compares results to the perfect information case from solving exact a posteriori solutions for sampled vehicle routing problems. The confidence interval for the overall mean difference is (3.56%, 4.11%). This paper examines approximate dynamic programming algorithms for the single-vehicle routing problem with stochastic demands from a dynamic or reoptimization perspective. The methods extend the rollout algorithm by implementing different base sequences (i.e. a priori solutions), look-ahead policies, and pruning schemes. The paper also considers computing the cost-to-go with Monte Carlo simulation in addition to direct approaches. The best new method found is a two-step lookahead rollout started with a stochastic base sequence. The routing cost is about 4.8% less than the one-step rollout algorithm started with a deterministic sequence. Results also show that Monte Carlo cost-to-go estimation reduces computation time 65% in large instances with little or no loss in solution quality. Moreover, the paper compares results to the perfect information case from solving exact a posteriori solutions for sampled vehicle routing problems. The confidence interval for the overall mean difference is (3.56%, 4.11%). [PUBLICATION ABSTRACT] This paper examines approximate dynamic programming algorithms for the single-vehicle routing problem with stochastic demands from a dynamic or reoptimization perspective. The methods extend the rollout algorithm by implementing different base sequences (i.e. a priori solutions), look-ahead policies, and pruning schemes. The paper also considers computing the cost-to-go with Monte Carlo simulation in addition to direct approaches. The best new method found is a two-step lookahead rollout started with a stochastic base sequence. The routing cost is about 4.8% less than the one-step rollout algorithm started with a deterministic sequence. Results also show that Monte Carlo cost-to-go estimation reduces computation time 65% in large instances with little or no loss in solution quality. Moreover, the paper compares results to the perfect information case from solving exact a posteriori solutions for sampled vehicle routing problems. The confidence interval for the overall mean difference is (3.56%, 4.11%).
Author	Storer, Robert Novoa, Clara
Author_xml	– sequence: 1 givenname: Clara surname: Novoa fullname: Novoa, Clara email: cn17@txstate.edu organization: Texas State University, Ingram School of Engineering, Industrial Engineering Program, San Marcos, TX 78666, USA – sequence: 2 givenname: Robert surname: Storer fullname: Storer, Robert email: rhs2@lehigh.edu organization: Industrial and Systems Engineering Department, Lehigh University, Bethlehem, PA 18015, USA
BackLink	http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=21235489$$DView record in Pascal Francis http://econpapers.repec.org/article/eeeejores/v_3a196_3ay_3a2009_3ai_3a2_3ap_3a509-515.htm$$DView record in RePEc
BookMark	eNp9UU2P1DAMjdAiMbvwBzhVSBxbkjSdpBKX1YovsRIXOEdp6m5TtUlJMgPz73HVhQOHjeQ4st97duxrcuWDB0JeM1oxyo7vpgqmECtOqapoXVFePyMHpiQvj-pIr8iB1lKWnDP5glynNFFKWcOaA7G3vjDrGsNvt5gMRX_xZnG2wMhDNMvi_MOeN3YshhCLPEJxhtHZGYoYTnkDYLqbYSl-uTwWKQc7mpRRpIfF-D69JM8HMyd49ehvyI-PH77ffS7vv336cnd7X1rBm1wq6Dn00rSip62gTAlDlRLS1h1TQy9Z0zZ2aMBgrB2ablBSdiCHTnHRUkXrG_Jm18V-fp4gZT2FU_RYUnMqkC7YBvq6gyKsYPUa8d_xogEPThCSPuvasPaI9wUNJ9qic9sTbUVrMIKz02NeUO3tY0mTrJmHaLx16Z8qZ7xuhGoRp3acjSGlCIO2Lpvsgs_RuFkzqrc96klvXehtj5rWGveIVP4f9a_6k6T3Owlw3mcHUSfrwFvoXQSbdR_cU_Q_6IG5VQ
CODEN	EJORDT
CitedBy_id	crossref_primary_10_1016_j_trpro_2017_03_015 crossref_primary_10_1371_journal_pone_0155176 crossref_primary_10_1016_j_ejor_2012_08_015 crossref_primary_10_1016_j_omega_2014_09_010 crossref_primary_10_1002_nav_22234 crossref_primary_10_1016_j_ejor_2018_03_034 crossref_primary_10_1016_j_knosys_2021_107378 crossref_primary_10_1080_00207179_2016_1144237 crossref_primary_10_1007_s10957_011_9902_7 crossref_primary_10_1287_trsc_2016_0709 crossref_primary_10_1016_j_cor_2014_03_027 crossref_primary_10_1016_j_eswa_2015_10_012 crossref_primary_10_1080_23302674_2020_1865475 crossref_primary_10_1093_imaman_dpv024 crossref_primary_10_1016_j_ejor_2016_09_040 crossref_primary_10_1109_TITS_2019_2934423 crossref_primary_10_1016_j_ijpe_2016_03_014 crossref_primary_10_1080_00207543_2015_1057625 crossref_primary_10_1155_2018_9848104 crossref_primary_10_1111_itor_12965 crossref_primary_10_1287_trsc_2013_0510 crossref_primary_10_1007_s00500_014_1257_1 crossref_primary_10_1016_j_trc_2022_103782 crossref_primary_10_1109_TITS_2020_3030218 crossref_primary_10_1016_j_cor_2012_12_015 crossref_primary_10_1016_j_tre_2017_11_005 crossref_primary_10_1287_trsc_2017_0761 crossref_primary_10_1080_09720502_2014_914284 crossref_primary_10_1155_2015_901583 crossref_primary_10_1260_1748_3018_9_4_449 crossref_primary_10_1007_s12351_017_0314_9 crossref_primary_10_1155_2018_1092092 crossref_primary_10_1016_j_compind_2020_103323 crossref_primary_10_1108_IJLM_05_2017_0109 crossref_primary_10_1109_TSG_2019_2918524 crossref_primary_10_3390_electronics12194167 crossref_primary_10_3390_math9131572 crossref_primary_10_1016_j_tre_2021_102464 crossref_primary_10_1080_00207543_2016_1201221 crossref_primary_10_1016_j_ins_2018_11_006 crossref_primary_10_1287_trsc_2017_0767 crossref_primary_10_1109_TAES_2021_3057649 crossref_primary_10_1016_j_cor_2017_02_008 crossref_primary_10_1016_j_asoc_2013_01_007 crossref_primary_10_1109_JOE_2022_3177858 crossref_primary_10_3390_a17050180 crossref_primary_10_1109_TITS_2016_2520918 crossref_primary_10_1002_net_21628 crossref_primary_10_1108_02635571211278947 crossref_primary_10_1142_S0219649214500221 crossref_primary_10_1016_j_ejor_2018_10_045 crossref_primary_10_1007_s10729_016_9388_9 crossref_primary_10_1109_TEM_2022_3209962 crossref_primary_10_1177_03611981241236479 crossref_primary_10_1016_j_iswa_2023_200225 crossref_primary_10_1155_2021_6634132 crossref_primary_10_1007_s12351_019_00506_z crossref_primary_10_1016_j_cie_2021_107871 crossref_primary_10_1080_0305215X_2019_1570180 crossref_primary_10_1155_2016_2804525 crossref_primary_10_3389_fphy_2022_835412 crossref_primary_10_1109_ACCESS_2023_3328404 crossref_primary_10_1080_23302674_2024_2365239 crossref_primary_10_3390_math12010028 crossref_primary_10_1287_trsc_2022_1129 crossref_primary_10_1016_j_trb_2015_06_008 crossref_primary_10_1109_TAC_2019_2906423 crossref_primary_10_1080_01605682_2023_2219693 crossref_primary_10_1155_2013_672078 crossref_primary_10_1287_trsc_2018_0840 crossref_primary_10_1016_j_cie_2022_108837 crossref_primary_10_1016_j_ijpe_2022_108751 crossref_primary_10_1080_01446193_2019_1608369 crossref_primary_10_3390_math10152699 crossref_primary_10_1108_BPMJ_02_2017_0047 crossref_primary_10_1287_trsc_2018_0876 crossref_primary_10_3390_data7050054 crossref_primary_10_1016_j_cor_2023_106338 crossref_primary_10_1007_s12351_021_00655_0 crossref_primary_10_1016_j_cor_2022_105884 crossref_primary_10_1016_j_ejor_2011_12_030 crossref_primary_10_1016_j_ejor_2018_09_027 crossref_primary_10_1080_00207543_2015_1043403 crossref_primary_10_1016_j_tre_2016_09_002 crossref_primary_10_1016_j_ejor_2015_08_050 crossref_primary_10_1109_TR_2019_2916898 crossref_primary_10_1007_s11067_015_9315_5 crossref_primary_10_1016_j_trc_2010_09_007 crossref_primary_10_1016_j_ejor_2014_04_024 crossref_primary_10_1007_s10479_011_0918_z crossref_primary_10_1016_j_biosystemseng_2018_04_003 crossref_primary_10_1287_opre_1120_1127 crossref_primary_10_1016_j_tre_2021_102358 crossref_primary_10_1287_trsc_2022_0099 crossref_primary_10_1016_j_cie_2015_12_007 crossref_primary_10_1007_s00291_020_00609_6 crossref_primary_10_3390_su12135333 crossref_primary_10_1016_j_jocs_2019_04_003 crossref_primary_10_1109_TITS_2025_3562860 crossref_primary_10_1016_j_trc_2019_12_020 crossref_primary_10_1109_TITS_2016_2521779 crossref_primary_10_3390_su162310378 crossref_primary_10_3390_pr10081488 crossref_primary_10_1287_trsc_2016_0719 crossref_primary_10_1109_TITS_2024_3438788 crossref_primary_10_1007_s10479_022_04674_8 crossref_primary_10_1016_j_cie_2023_109822 crossref_primary_10_11627_jksie_2024_47_2_168 crossref_primary_10_1016_j_trc_2024_104801 crossref_primary_10_1155_2016_8461857 crossref_primary_10_1155_2021_9589476 crossref_primary_10_1109_TITS_2024_3357060 crossref_primary_10_1287_opre_1100_0857 crossref_primary_10_3390_app14198642 crossref_primary_10_3390_sym11040546 crossref_primary_10_1287_trsc_2016_0682 crossref_primary_10_1007_s11831_021_09574_x crossref_primary_10_1016_j_heliyon_2024_e31758 crossref_primary_10_1109_ACCESS_2017_2769666 crossref_primary_10_1016_j_cie_2011_10_001 crossref_primary_10_1080_00207721_2011_618646 crossref_primary_10_1051_matecconf_201925203003 crossref_primary_10_1287_trsc_2015_0591 crossref_primary_10_1016_j_ejor_2021_07_014 crossref_primary_10_1080_23270012_2020_1811166 crossref_primary_10_12677_OJTT_2021_104034 crossref_primary_10_1007_s10696_024_09551_z crossref_primary_10_3390_su9020288 crossref_primary_10_1002_mcda_1519 crossref_primary_10_1016_j_ejor_2015_02_038 crossref_primary_10_3138_infor_51_1_31 crossref_primary_10_1016_j_trd_2017_04_016 crossref_primary_10_1287_trsc_2018_0887 crossref_primary_10_1016_j_jairtraman_2023_102397 crossref_primary_10_1016_j_tre_2021_102496 crossref_primary_10_1299_kikaic_76_3220 crossref_primary_10_1016_j_ejor_2021_09_019 crossref_primary_10_3233_IFS_151578 crossref_primary_10_1016_j_tre_2015_11_004
Cites_doi	10.1287/trsc.23.3.166 10.1287/opre.51.6.850.24925 10.1080/03081069208717490 10.1287/ijoc.1040.0079 10.1016/0377-2217(95)00050-X 10.1287/trsc.36.1.94.574 10.1007/BF02022035 10.1287/trsc.33.4.381 10.1287/trsc.29.4.342 10.1016/0377-2217(89)90354-8 10.1287/opre.44.2.286 10.1023/A:1009634810396 10.1287/trsc.34.1.99.12278 10.1023/A:1009635226865 10.1287/opre.40.3.574 10.1287/trsc.1050.0114 10.1007/s10479-005-5729-7 10.1016/S0305-0548(99)00146-X 10.1287/opre.49.5.796.10608 10.1287/trsc.29.2.143 10.1016/0377-2217(92)90323-2 10.1023/A:1025605803490 10.1016/0377-2217(93)90132-7 10.1007/s10107-002-0323-0 10.1007/BF02098286 10.1287/opre.1040.0114 10.1023/A:1018995927636 10.1287/opre.1060.0347 10.1016/S0166-218X(01)00351-1 10.1287/opre.50.3.415.7751
ContentType	Journal Article
Copyright	2008 Elsevier B.V. 2009 INIST-CNRS Copyright Elsevier Sequoia S.A. Jul 16, 2009
Copyright_xml	– notice: 2008 Elsevier B.V. – notice: 2009 INIST-CNRS – notice: Copyright Elsevier Sequoia S.A. Jul 16, 2009
DBID	AAYXX CITATION IQODW DKI X2L 7SC 7TB 8FD FR3 JQ2 L7M L~C L~D
DOI	10.1016/j.ejor.2008.03.023
DatabaseName	CrossRef Pascal-Francis RePEc IDEAS RePEc Computer and Information Systems Abstracts Mechanical & Transportation Engineering Abstracts Technology Research Database Engineering Research Database ProQuest Computer Science Collection Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional
DatabaseTitle	CrossRef Technology Research Database Computer and Information Systems Abstracts – Academic Mechanical & Transportation Engineering Abstracts ProQuest Computer Science Collection Computer and Information Systems Abstracts Engineering Research Database Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Professional
DatabaseTitleList	Technology Research Database
DeliveryMethod	fulltext_linktorsrc
Discipline	Engineering Computer Science Business Applied Sciences
EISSN	1872-6860
EndPage	515
ExternalDocumentID	1627811241 eeeejores_v_3a196_3ay_3a2009_3ai_3a2_3ap_3a509_515_htm 21235489 10_1016_j_ejor_2008_03_023 S0377221708003172
Genre	Feature
GroupedDBID	--K --M -~X .DC .~1 0R~ 1B1 1OL 1RT 1~. 1~5 29G 4.4 41~ 457 4G. 5GY 5VS 6OB 7-5 71M 8P~ 9JN 9JO AAAKF AAAKG AABNK AACTN AAEDT AAEDW AAIAV AAIKJ AAKOC AALRI AAOAW AAQFI AAQXK AARIN AAXUO AAYFN AAYOK ABAOU ABBOA ABFNM ABFRF ABJNI ABMAC ABUCO ABXDB ABYKQ ACAZW ACDAQ ACGFO ACGFS ACIWK ACNCT ACNNM ACRLP ACZNC ADBBV ADEZE ADGUI ADIYS ADJOM ADMUD AEBSH AEFWE AEKER AENEX AFFNX AFKWA AFTJW AGHFR AGUBO AGYEJ AHHHB AHZHX AI. AIALX AIEXJ AIGVJ AIKHN AITUG AJBFU AJOXV ALMA_UNASSIGNED_HOLDINGS AMFUW AMRAJ AOUOD APLSM ARUGR ASPBG AVWKF AXJTR AZFZN BKOJK BKOMP BLXMC CS3 DU5 EBS EFJIC EFLBG EJD EO8 EO9 EP2 EP3 F5P FDB FEDTE FGOYB FIRID FNPLU FYGXN G-Q GBLVA GBOLZ HAMUX HVGLF HZ~ IHE J1W KOM LY1 M41 MHUIS MO0 MS~ N9A O-L O9- OAUVE OZT P-8 P-9 P2P PC. PQQKQ Q38 R2- RIG ROL RPZ RXW SCC SDF SDG SDP SDS SES SEW SPC SPCBC SSB SSD SSV SSW SSZ T5K TAE TN5 U5U VH1 WUQ XPP ZMT ~02 ~G- 9DU AATTM AAXKI AAYWO AAYXX ABWVN ACLOT ACRPL ACVFH ADCNI ADNMO ADXHL AEIPS AEUPX AFJKZ AFPUW AGQPQ AIGII AIIUN AKBMS AKRWK AKYEP ANKPU APXCP CITATION EFKBS ~HD AFXIZ AGCQF AGRNS BNPGV IQODW SSH 02 08R 0R 1 41 6XO 8P AAPBV ABFLS ADALY DKI G- HZ IPNFZ K M MS PQEST STF X X2L 7SC 7TB 8FD FR3 JQ2 L7M L~C L~D
ID	FETCH-LOGICAL-c425t-8ed2ed7a94d0940184a08847c3b18fd71595cf5ea8479f5bf877be7fb82490803
ISICitedReferencesCount	191
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000263206800012&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	0377-2217
IngestDate	Sun Nov 30 04:10:13 EST 2025 Wed Aug 18 03:50:56 EDT 2021 Mon Jul 21 09:17:16 EDT 2025 Tue Nov 18 21:23:31 EST 2025 Sat Nov 29 01:40:55 EST 2025 Fri Feb 23 02:27:49 EST 2024
IsPeerReviewed	true
IsScholarly	true
Issue	2
Keywords	Stochastic vehicle routing Approximate dynamic programming Transportation Monte Carlo method Filtering Vehicle routing problem Routing Modeling Confidence interval Exact solution Computation time Pruning(tree) Cost estimation Dynamic programming
Language	English
License	https://www.elsevier.com/tdm/userlicense/1.0 CC BY 4.0
LinkModel	OpenURL
MergedId	FETCHMERGED-LOGICAL-c425t-8ed2ed7a94d0940184a08847c3b18fd71595cf5ea8479f5bf877be7fb82490803
Notes	SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14
PQID	204159410
PQPubID	45678
PageCount	7
ParticipantIDs	proquest_journals_204159410 repec_primary_eeeejores_v_3a196_3ay_3a2009_3ai_3a2_3ap_3a509_515_htm pascalfrancis_primary_21235489 crossref_citationtrail_10_1016_j_ejor_2008_03_023 crossref_primary_10_1016_j_ejor_2008_03_023 elsevier_sciencedirect_doi_10_1016_j_ejor_2008_03_023
PublicationCentury	2000
PublicationDate	2009-07-16
PublicationDateYYYYMMDD	2009-07-16
PublicationDate_xml	– month: 07 year: 2009 text: 2009-07-16 day: 16
PublicationDecade	2000
PublicationPlace	Amsterdam
PublicationPlace_xml	– name: Amsterdam
PublicationSeriesTitle	European Journal of Operational Research
PublicationTitle	European journal of operational research
PublicationYear	2009
Publisher	Elsevier B.V Elsevier Elsevier Sequoia S.A
Publisher_xml	– name: Elsevier B.V – name: Elsevier – name: Elsevier Sequoia S.A
References	Chepuri, Homem-De-Mello (bib12) 2005; 134 Dror, Laporte, Trudeau (bib17) 1989; 23 Adelman (bib1) 2004; 52 Gendreau, Guertin, Potvin, Taillard (bib19) 1999; 33 Sutton, Barto (bib43) 1998 Bianchi, Birattari, Chiarandini, Manfrin, Mastrolilli, Paquete, Rossi-Doria, Schiavinotto (bib11) 2004 Bastian, Rinnooy Kan (bib2) 1992; 56 Secomandi (bib40) 2001; 49 Marković, H., Ćavar, I., Carić, T., 2005. Using data mining to forecast uncertain demands in stochastic vehicle routing problem. In: 13th International Symposium on Elecronics in Transport (ISEP), Slovenia, pp. 1–6. Novoa, C., 2005. Static and dynamic approaches for solving the vehicle routing problem with stochastic demands. Ph.D. Thesis, Department of Industrial and Systems Engineering, Lehigh University, Bethlehem, PA. Psaraftis (bib34) 1995; 61 Ladányi, Ralphs, Trotter (bib25) 2001 de Farias, Van-Roy (bib13) 2003; 51 Bertsekas, Tsitsiklis, Wu (bib7) 1997; 3 Gendreau, Laporte, Séguin (bib20) 1995; 29 Bertsekas, Tsitsiklis (bib6) 1996 Van-Roy, B., Bertsekas, D.P., Lee, Y., Tsitsiklis, J.N., 1998. A neuro-dynamic approach to retailer inventory management. Technical Report, R-96, Laboratory for Information and Decision Systems, Massachusetts Institute of Technology. Dror (bib15) 1993; 64 Ichoua, Gendreau, Potvin (bib23) 2006; 40 . Toth, Vigo (bib47) 2002; 123 Bertsimas (bib8) 1992; 40 Bertsimas, Simchi-Levi (bib10) 1996; 44 Ralphs, Kopman, Pulleyblank, Trotter (bib36) 2003; 94 Bertsimas, Chervi, Peterson (bib9) 1995; 29 Dror, Ball, Golden (bib16) 1985; 4 Secomandi, N., 1998. Exact and heuristic dynamic programming algorithms for the vehicle routing problem with stochastic demands. Ph.D. Thesis, Department of Decision and Information Sciences, University of Houston, Houston, TX. Bertsekas (bib4) 2001; vol. 2 Secomandi, N., Margot, F., in review. Reoptimization approaches for the vehicle problem with stochastic demands, Operations Research Yang, Mathur, Ballou (bib49) 2000; 34 Secomandi (bib39) 2000; 27 Hjorring, Holt (bib22) 1999; 86 Bertsekas, Castanon (bib5) 1999 Dessouky, Ordoñez, Jia, Shen (bib14) 2005 Novoa, C., Berger, R., Linderoth, J., Storer, R., 2006. A set-partitioning-based model for the stochastic vehicle routing problem. Technical Report, 06T-008, Industrial and Systems Engineering, Lehigh University. Teodorovic, Pavkovic (bib44) 1992; 16 Erera, A.L., Savelsbergh, M., Uyar, E., 2007. Fixed routes with backup vehicles for stochastic vehicle routing problems with time constraints. Technical Report, The Supply Chain and Logistics Institute, School of Industrial and Systems Engineering, Georgia Institute of Technology. and at Topaloglu, Powell (bib45) 2006; 18 Kleywegt, Nori, Savelsbergh (bib24) 2002; 36 Ralphs, T.K., 2006. SYMPHONY User’s Manual, Available at Powell (bib32) 2007 Laporte, Louveaux, Mercure (bib26) 1989; 39 Secomandi (bib41) 2003; 9 Bertsekas (bib3) 2000; vol. 1 Topaloglu, Powell (bib46) 2007; 55 Gendreau, Laporte, Séguin (bib21) 1996; 88 Powell, Jaillet, Odoni (bib33) 1995; 8 Nemhauser, Wolsey (bib29) 1999 Savelsbergh, Goetschalckx (bib37) 1995; 16 Laporte, Louveaux, Van-Hamme (bib27) 2002; 50 Dror (10.1016/j.ejor.2008.03.023_bib15) 1993; 64 Yang (10.1016/j.ejor.2008.03.023_bib49) 2000; 34 Laporte (10.1016/j.ejor.2008.03.023_bib26) 1989; 39 Gendreau (10.1016/j.ejor.2008.03.023_bib21) 1996; 88 Dror (10.1016/j.ejor.2008.03.023_bib17) 1989; 23 Topaloglu (10.1016/j.ejor.2008.03.023_bib46) 2007; 55 Bertsekas (10.1016/j.ejor.2008.03.023_bib7) 1997; 3 Chepuri (10.1016/j.ejor.2008.03.023_bib12) 2005; 134 Bertsimas (10.1016/j.ejor.2008.03.023_bib10) 1996; 44 Gendreau (10.1016/j.ejor.2008.03.023_bib20) 1995; 29 Secomandi (10.1016/j.ejor.2008.03.023_bib39) 2000; 27 10.1016/j.ejor.2008.03.023_bib28 Ralphs (10.1016/j.ejor.2008.03.023_bib36) 2003; 94 Sutton (10.1016/j.ejor.2008.03.023_bib43) 1998 Kleywegt (10.1016/j.ejor.2008.03.023_bib24) 2002; 36 Powell (10.1016/j.ejor.2008.03.023_bib32) 2007 Bertsekas (10.1016/j.ejor.2008.03.023_bib6) 1996 Bastian (10.1016/j.ejor.2008.03.023_bib2) 1992; 56 Bertsimas (10.1016/j.ejor.2008.03.023_bib9) 1995; 29 Toth (10.1016/j.ejor.2008.03.023_bib47) 2002; 123 10.1016/j.ejor.2008.03.023_bib18 Topaloglu (10.1016/j.ejor.2008.03.023_bib45) 2006; 18 Secomandi (10.1016/j.ejor.2008.03.023_bib41) 2003; 9 Adelman (10.1016/j.ejor.2008.03.023_bib1) 2004; 52 Ladányi (10.1016/j.ejor.2008.03.023_bib25) 2001 Bertsekas (10.1016/j.ejor.2008.03.023_bib5) 1999 Bertsekas (10.1016/j.ejor.2008.03.023_bib3) 2000; vol. 1 10.1016/j.ejor.2008.03.023_bib42 Secomandi (10.1016/j.ejor.2008.03.023_bib40) 2001; 49 Ichoua (10.1016/j.ejor.2008.03.023_bib23) 2006; 40 Bianchi (10.1016/j.ejor.2008.03.023_bib11) 2004 Bertsimas (10.1016/j.ejor.2008.03.023_bib8) 1992; 40 Savelsbergh (10.1016/j.ejor.2008.03.023_bib37) 1995; 16 Dror (10.1016/j.ejor.2008.03.023_bib16) 1985; 4 10.1016/j.ejor.2008.03.023_bib48 Bertsekas (10.1016/j.ejor.2008.03.023_bib4) 2001; vol. 2 Laporte (10.1016/j.ejor.2008.03.023_bib27) 2002; 50 Teodorovic (10.1016/j.ejor.2008.03.023_bib44) 1992; 16 Powell (10.1016/j.ejor.2008.03.023_bib33) 1995; 8 Nemhauser (10.1016/j.ejor.2008.03.023_bib29) 1999 Dessouky (10.1016/j.ejor.2008.03.023_bib14) 2005 de Farias (10.1016/j.ejor.2008.03.023_bib13) 2003; 51 Hjorring (10.1016/j.ejor.2008.03.023_bib22) 1999; 86 10.1016/j.ejor.2008.03.023_bib31 10.1016/j.ejor.2008.03.023_bib30 10.1016/j.ejor.2008.03.023_bib35 10.1016/j.ejor.2008.03.023_bib38 Gendreau (10.1016/j.ejor.2008.03.023_bib19) 1999; 33 Psaraftis (10.1016/j.ejor.2008.03.023_bib34) 1995; 61
References_xml	– volume: 52 start-page: 499 year: 2004 end-page: 504 ident: bib1 article-title: A price-directed approach to stochastic inventory routing publication-title: Operations Research – volume: 33 start-page: 381 year: 1999 end-page: 390 ident: bib19 article-title: Parallel tabu search for real-time vehicle routing and dispatching publication-title: Transportation Science – volume: 3 start-page: 245 year: 1997 end-page: 262 ident: bib7 article-title: Rollout algorithms for combinatorial optimization publication-title: Journal of Heuristics – volume: 40 start-page: 574 year: 1992 end-page: 585 ident: bib8 article-title: A vehicle routing problem with stochastic demand publication-title: Operations Research – volume: 55 start-page: 319 year: 2007 end-page: 350 ident: bib46 article-title: Sensitivity analysis of a dynamic fleet management model using approximate dynamic programming publication-title: Operations Research – start-page: 309 year: 2005 end-page: 339 ident: bib14 article-title: Rapid Distribution of Medical Supplies publication-title: Patient Flow: Reducing Delay Management in Health Care Systems – volume: 88 start-page: 3 year: 1996 end-page: 12 ident: bib21 article-title: Invited review: Stochastic vehicle routing publication-title: European Journal of Operational Research – reference: and at – volume: 27 start-page: 1201 year: 2000 end-page: 1225 ident: bib39 article-title: Comparing neuro-dynamic programming algorithms for the vehicle routing problem with stochastic demands publication-title: Computers and Operations Research – volume: 39 start-page: 71 year: 1989 end-page: 78 ident: bib26 article-title: Models and exact solutions for a class of stochastic location-routing problems publication-title: European Journal of Operational Research – volume: 16 start-page: 163 year: 1995 end-page: 188 ident: bib37 article-title: A comparison of the efficiency of fixed versus variable vehicle routes publication-title: Journal of Business Logistics – volume: 44 start-page: 286 year: 1996 end-page: 304 ident: bib10 article-title: A new generation of vehicle routing research: Robust algorithms, addressing uncertainty publication-title: Operations Research – volume: 36 start-page: 94 year: 2002 end-page: 118 ident: bib24 article-title: The stochastic inventory routing problem with direct deliveries publication-title: Transportation Science – volume: 29 start-page: 342 year: 1995 end-page: 352 ident: bib9 article-title: Computational approaches to stochastic vehicle routing problems publication-title: Transportation Science – reference: Secomandi, N., Margot, F., in review. Reoptimization approaches for the vehicle problem with stochastic demands, Operations Research – reference: Secomandi, N., 1998. Exact and heuristic dynamic programming algorithms for the vehicle routing problem with stochastic demands. Ph.D. Thesis, Department of Decision and Information Sciences, University of Houston, Houston, TX. – reference: Novoa, C., Berger, R., Linderoth, J., Storer, R., 2006. A set-partitioning-based model for the stochastic vehicle routing problem. Technical Report, 06T-008, Industrial and Systems Engineering, Lehigh University. – volume: 94 start-page: 343 year: 2003 end-page: 359 ident: bib36 article-title: On the capacitated vehicle routing problem publication-title: Mathematical Programming – volume: 4 start-page: 3 year: 1985 end-page: 23 ident: bib16 article-title: A computational comparison of algorithms for the inventory routing problem publication-title: Annals of Operations Research – volume: 40 start-page: 211 year: 2006 end-page: 225 ident: bib23 article-title: Exploiting knowledge about future demands for real-time vehicle dispatching publication-title: Transportation Science – reference: Novoa, C., 2005. Static and dynamic approaches for solving the vehicle routing problem with stochastic demands. Ph.D. Thesis, Department of Industrial and Systems Engineering, Lehigh University, Bethlehem, PA. – year: 1999 ident: bib29 article-title: Integer and Combinatorial Optimization – reference: . – volume: 64 start-page: 432 year: 1993 end-page: 441 ident: bib15 article-title: Modeling vehicle routing with uncertain demands as a stochastic program: Properties of the corresponding solution publication-title: European Journal of Operational Research – volume: 51 start-page: 850 year: 2003 end-page: 865 ident: bib13 article-title: The linear programming approach to approximate dynamic programming publication-title: Operations Research – reference: Marković, H., Ćavar, I., Carić, T., 2005. Using data mining to forecast uncertain demands in stochastic vehicle routing problem. In: 13th International Symposium on Elecronics in Transport (ISEP), Slovenia, pp. 1–6. – volume: vol. 1 year: 2000 ident: bib3 publication-title: Dynamic Programming and Optimal Control – year: 2004 ident: bib11 publication-title: Metaheuristics for the vehicle routing problem with stochastic demands. Parallel problem solving from nature PPSN VIII – volume: 56 start-page: 407 year: 1992 end-page: 412 ident: bib2 article-title: The stochastic vehicle routing problem revisited publication-title: European Journal of Operational Research – volume: 23 start-page: 166 year: 1989 end-page: 176 ident: bib17 article-title: Vehicle routing with stochastic demands: Properties and solution frameworks publication-title: Transportation Science – volume: 50 start-page: 415 year: 2002 end-page: 423 ident: bib27 article-title: An integer L-Shaped algorithm for the capacitated vehicle routing problem with stochastic demands publication-title: Operations Research – reference: Ralphs, T.K., 2006. SYMPHONY User’s Manual, Available at – volume: 34 start-page: 99 year: 2000 end-page: 112 ident: bib49 article-title: Stochastic vehicle routing problem with restocking publication-title: Transportation Science – volume: 134 start-page: 153 year: 2005 end-page: 181 ident: bib12 article-title: Solving the vehicle routing problem with stochastic demands using the cross entropy method publication-title: Annals of Operations Research – volume: 8 start-page: 141 year: 1995 end-page: 295 ident: bib33 article-title: Stochastic and dynamic networks and routing publication-title: Network routing – volume: 16 start-page: 261 year: 1992 end-page: 273 ident: bib44 article-title: A simulated annealing technique approach to the vehicle routing problem in the case of stochastic demand publication-title: Transportation Planning and Technology – reference: Erera, A.L., Savelsbergh, M., Uyar, E., 2007. Fixed routes with backup vehicles for stochastic vehicle routing problems with time constraints. Technical Report, The Supply Chain and Logistics Institute, School of Industrial and Systems Engineering, Georgia Institute of Technology. – volume: 61 start-page: 143 year: 1995 end-page: 164 ident: bib34 article-title: Dynamic vehicle routing: Status and prospects publication-title: Annals of Operations Research – volume: 49 start-page: 796 year: 2001 end-page: 802 ident: bib40 article-title: A rollout policy for the vehicle routing problem with stochastic demands publication-title: Operations Research – reference: Van-Roy, B., Bertsekas, D.P., Lee, Y., Tsitsiklis, J.N., 1998. A neuro-dynamic approach to retailer inventory management. Technical Report, R-96, Laboratory for Information and Decision Systems, Massachusetts Institute of Technology. – volume: 86 start-page: 569 year: 1999 end-page: 584 ident: bib22 article-title: New optimality cuts for a single-vehicle stochastic routing problem publication-title: Annals of Operations Research – year: 2007 ident: bib32 publication-title: Approximate dynamic programming: solving the curses of dimensionality – start-page: 89 year: 1999 end-page: 108 ident: bib5 article-title: Rollout algorithms for stochastic scheduling problems publication-title: Journal of Heuristics – volume: 29 start-page: 143 year: 1995 end-page: 155 ident: bib20 article-title: An exact algorithm for the vehicle routing problem with stochastic demands and customers publication-title: Transportation Science – volume: 18 start-page: 31 year: 2006 end-page: 42 ident: bib45 article-title: Dynamic programming approximations for stochastic, time-staged integer multicommodity flow problems publication-title: INFORMS Journal on Computing – start-page: 223 year: 2001 end-page: 260 ident: bib25 article-title: Branch cut and price: Sequential and parallel publication-title: Computational Combinatorial Optimization – volume: 9 start-page: 321 year: 2003 end-page: 352 ident: bib41 article-title: Analysis of a rollout approach to sequencing problems with stochastic routing applications publication-title: Journal of Heuristics – year: 1998 ident: bib43 article-title: Reinforcement Learning – year: 1996 ident: bib6 article-title: Neuro-Dynamic Programming – volume: 123 start-page: 487 year: 2002 end-page: 512 ident: bib47 article-title: Models, relaxations and exact approaches for the capacitated vehicle routing problem publication-title: Discrete Applied Mathematics – volume: vol. 2 year: 2001 ident: bib4 publication-title: Dynamic Programming and Optimal Control – volume: 23 start-page: 166 issue: 3 year: 1989 ident: 10.1016/j.ejor.2008.03.023_bib17 article-title: Vehicle routing with stochastic demands: Properties and solution frameworks publication-title: Transportation Science doi: 10.1287/trsc.23.3.166 – volume: 51 start-page: 850 issue: 6 year: 2003 ident: 10.1016/j.ejor.2008.03.023_bib13 article-title: The linear programming approach to approximate dynamic programming publication-title: Operations Research doi: 10.1287/opre.51.6.850.24925 – volume: vol. 2 year: 2001 ident: 10.1016/j.ejor.2008.03.023_bib4 – volume: 16 start-page: 261 year: 1992 ident: 10.1016/j.ejor.2008.03.023_bib44 article-title: A simulated annealing technique approach to the vehicle routing problem in the case of stochastic demand publication-title: Transportation Planning and Technology doi: 10.1080/03081069208717490 – year: 1998 ident: 10.1016/j.ejor.2008.03.023_bib43 – ident: 10.1016/j.ejor.2008.03.023_bib31 – volume: 18 start-page: 31 issue: 1 year: 2006 ident: 10.1016/j.ejor.2008.03.023_bib45 article-title: Dynamic programming approximations for stochastic, time-staged integer multicommodity flow problems publication-title: INFORMS Journal on Computing doi: 10.1287/ijoc.1040.0079 – ident: 10.1016/j.ejor.2008.03.023_bib35 – year: 1999 ident: 10.1016/j.ejor.2008.03.023_bib29 – volume: 88 start-page: 3 year: 1996 ident: 10.1016/j.ejor.2008.03.023_bib21 article-title: Invited review: Stochastic vehicle routing publication-title: European Journal of Operational Research doi: 10.1016/0377-2217(95)00050-X – volume: 36 start-page: 94 issue: 1 year: 2002 ident: 10.1016/j.ejor.2008.03.023_bib24 article-title: The stochastic inventory routing problem with direct deliveries publication-title: Transportation Science doi: 10.1287/trsc.36.1.94.574 – volume: 4 start-page: 3 year: 1985 ident: 10.1016/j.ejor.2008.03.023_bib16 article-title: A computational comparison of algorithms for the inventory routing problem publication-title: Annals of Operations Research doi: 10.1007/BF02022035 – volume: 33 start-page: 381 issue: 4 year: 1999 ident: 10.1016/j.ejor.2008.03.023_bib19 article-title: Parallel tabu search for real-time vehicle routing and dispatching publication-title: Transportation Science doi: 10.1287/trsc.33.4.381 – volume: 29 start-page: 342 issue: 4 year: 1995 ident: 10.1016/j.ejor.2008.03.023_bib9 article-title: Computational approaches to stochastic vehicle routing problems publication-title: Transportation Science doi: 10.1287/trsc.29.4.342 – volume: 39 start-page: 71 year: 1989 ident: 10.1016/j.ejor.2008.03.023_bib26 article-title: Models and exact solutions for a class of stochastic location-routing problems publication-title: European Journal of Operational Research doi: 10.1016/0377-2217(89)90354-8 – volume: 44 start-page: 286 issue: 2 year: 1996 ident: 10.1016/j.ejor.2008.03.023_bib10 article-title: A new generation of vehicle routing research: Robust algorithms, addressing uncertainty publication-title: Operations Research doi: 10.1287/opre.44.2.286 – year: 1996 ident: 10.1016/j.ejor.2008.03.023_bib6 – start-page: 89 year: 1999 ident: 10.1016/j.ejor.2008.03.023_bib5 article-title: Rollout algorithms for stochastic scheduling problems publication-title: Journal of Heuristics doi: 10.1023/A:1009634810396 – volume: 34 start-page: 99 issue: 1 year: 2000 ident: 10.1016/j.ejor.2008.03.023_bib49 article-title: Stochastic vehicle routing problem with restocking publication-title: Transportation Science doi: 10.1287/trsc.34.1.99.12278 – volume: 3 start-page: 245 year: 1997 ident: 10.1016/j.ejor.2008.03.023_bib7 article-title: Rollout algorithms for combinatorial optimization publication-title: Journal of Heuristics doi: 10.1023/A:1009635226865 – volume: 40 start-page: 574 issue: 3 year: 1992 ident: 10.1016/j.ejor.2008.03.023_bib8 article-title: A vehicle routing problem with stochastic demand publication-title: Operations Research doi: 10.1287/opre.40.3.574 – volume: 40 start-page: 211 issue: 2 year: 2006 ident: 10.1016/j.ejor.2008.03.023_bib23 article-title: Exploiting knowledge about future demands for real-time vehicle dispatching publication-title: Transportation Science doi: 10.1287/trsc.1050.0114 – ident: 10.1016/j.ejor.2008.03.023_bib42 – volume: 134 start-page: 153 year: 2005 ident: 10.1016/j.ejor.2008.03.023_bib12 article-title: Solving the vehicle routing problem with stochastic demands using the cross entropy method publication-title: Annals of Operations Research doi: 10.1007/s10479-005-5729-7 – volume: vol. 1 year: 2000 ident: 10.1016/j.ejor.2008.03.023_bib3 – ident: 10.1016/j.ejor.2008.03.023_bib18 – year: 2004 ident: 10.1016/j.ejor.2008.03.023_bib11 – start-page: 223 year: 2001 ident: 10.1016/j.ejor.2008.03.023_bib25 article-title: Branch cut and price: Sequential and parallel – volume: 27 start-page: 1201 year: 2000 ident: 10.1016/j.ejor.2008.03.023_bib39 article-title: Comparing neuro-dynamic programming algorithms for the vehicle routing problem with stochastic demands publication-title: Computers and Operations Research doi: 10.1016/S0305-0548(99)00146-X – volume: 49 start-page: 796 issue: 5 year: 2001 ident: 10.1016/j.ejor.2008.03.023_bib40 article-title: A rollout policy for the vehicle routing problem with stochastic demands publication-title: Operations Research doi: 10.1287/opre.49.5.796.10608 – volume: 29 start-page: 143 issue: 2 year: 1995 ident: 10.1016/j.ejor.2008.03.023_bib20 article-title: An exact algorithm for the vehicle routing problem with stochastic demands and customers publication-title: Transportation Science doi: 10.1287/trsc.29.2.143 – volume: 56 start-page: 407 year: 1992 ident: 10.1016/j.ejor.2008.03.023_bib2 article-title: The stochastic vehicle routing problem revisited publication-title: European Journal of Operational Research doi: 10.1016/0377-2217(92)90323-2 – volume: 9 start-page: 321 year: 2003 ident: 10.1016/j.ejor.2008.03.023_bib41 article-title: Analysis of a rollout approach to sequencing problems with stochastic routing applications publication-title: Journal of Heuristics doi: 10.1023/A:1025605803490 – volume: 64 start-page: 432 year: 1993 ident: 10.1016/j.ejor.2008.03.023_bib15 article-title: Modeling vehicle routing with uncertain demands as a stochastic program: Properties of the corresponding solution publication-title: European Journal of Operational Research doi: 10.1016/0377-2217(93)90132-7 – volume: 94 start-page: 343 issue: 2–3 year: 2003 ident: 10.1016/j.ejor.2008.03.023_bib36 article-title: On the capacitated vehicle routing problem publication-title: Mathematical Programming doi: 10.1007/s10107-002-0323-0 – volume: 16 start-page: 163 year: 1995 ident: 10.1016/j.ejor.2008.03.023_bib37 article-title: A comparison of the efficiency of fixed versus variable vehicle routes publication-title: Journal of Business Logistics – ident: 10.1016/j.ejor.2008.03.023_bib28 – volume: 61 start-page: 143 year: 1995 ident: 10.1016/j.ejor.2008.03.023_bib34 article-title: Dynamic vehicle routing: Status and prospects publication-title: Annals of Operations Research doi: 10.1007/BF02098286 – volume: 52 start-page: 499 issue: 4 year: 2004 ident: 10.1016/j.ejor.2008.03.023_bib1 article-title: A price-directed approach to stochastic inventory routing publication-title: Operations Research doi: 10.1287/opre.1040.0114 – volume: 86 start-page: 569 year: 1999 ident: 10.1016/j.ejor.2008.03.023_bib22 article-title: New optimality cuts for a single-vehicle stochastic routing problem publication-title: Annals of Operations Research doi: 10.1023/A:1018995927636 – ident: 10.1016/j.ejor.2008.03.023_bib30 – volume: 55 start-page: 319 issue: 2 year: 2007 ident: 10.1016/j.ejor.2008.03.023_bib46 article-title: Sensitivity analysis of a dynamic fleet management model using approximate dynamic programming publication-title: Operations Research doi: 10.1287/opre.1060.0347 – ident: 10.1016/j.ejor.2008.03.023_bib38 – start-page: 309 year: 2005 ident: 10.1016/j.ejor.2008.03.023_bib14 article-title: Rapid Distribution of Medical Supplies – volume: 8 start-page: 141 year: 1995 ident: 10.1016/j.ejor.2008.03.023_bib33 article-title: Stochastic and dynamic networks and routing – year: 2007 ident: 10.1016/j.ejor.2008.03.023_bib32 – volume: 123 start-page: 487 year: 2002 ident: 10.1016/j.ejor.2008.03.023_bib47 article-title: Models, relaxations and exact approaches for the capacitated vehicle routing problem publication-title: Discrete Applied Mathematics doi: 10.1016/S0166-218X(01)00351-1 – volume: 50 start-page: 415 issue: 3 year: 2002 ident: 10.1016/j.ejor.2008.03.023_bib27 article-title: An integer L-Shaped algorithm for the capacitated vehicle routing problem with stochastic demands publication-title: Operations Research doi: 10.1287/opre.50.3.415.7751 – ident: 10.1016/j.ejor.2008.03.023_bib48
SSID	ssj0001515
Score	2.4171312
Snippet	This paper examines approximate dynamic programming algorithms for the single-vehicle routing problem with stochastic demands from a dynamic or reoptimization... This paper examines approximate dynamic programming algorithms for the single-vehicle routing problem with stochastic demands from a dynamic or reoptimization...
SourceID	proquest repec pascalfrancis crossref elsevier
SourceType	Aggregation Database Index Database Enrichment Source Publisher
StartPage	509
SubjectTerms	Applied sciences Approximate dynamic programming Dynamic programming Exact sciences and technology Logistics Monte Carlo simulation Operational research and scientific management Operational research. Management science Optimization algorithms Routing Stochastic models Stochastic vehicle routing Studies Transportation Transportation Stochastic vehicle routing Approximate dynamic programming
Title	An approximate dynamic programming approach for the vehicle routing problem with stochastic demands
URI	https://dx.doi.org/10.1016/j.ejor.2008.03.023 http://econpapers.repec.org/article/eeeejores/v_3a196_3ay_3a2009_3ai_3a2_3ap_3a509-515.htm https://www.proquest.com/docview/204159410
Volume	196
WOSCitedRecordID	wos000263206800012&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: PRVESC databaseName: Elsevier SD Freedom Collection Journals 2021 customDbUrl: eissn: 1872-6860 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0001515 issn: 0377-2217 databaseCode: AIEXJ dateStart: 19950105 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV3fb9MwELaqFSEQ4kcBrQwmP_BWpWqTuI4fKxgCHiakDalvVuJc1FZrUqVZVR73n3OO7TTdYAIkKiVNreZHe599X5z77gh5r0l1Mk7AS4ApDz8pT_AMPDESSShC9CFjVReb4Ofn0WwmvnU6N04Ls73ieR7tdmL9X02NbWhsLZ39C3M3B8UG3Eaj4xrNjus_Mvw0N4nCdwskozBITcl5F4i1qkWJNpF4E2O4hbk-zKAsrisjT6_LzNgA9qpQ81jncx6ksHLS4F9O51tqiw2lm2S02YT2s87FtqgJq44ManzCBd76QyvU-2AyQuufPKOVNDNkd1QyRpnFuef7RqM5BDPQRtz3JpGpJdCMxKa4rYWc3xpX2Ui0XDQzCtA7o7-ZiFgOYVmUNkw2GI6MnvlWVu0LfVH6mjRjRg6FXrzrcyZwYOxOv5zNvjbuXDO--lGU_RFWeWWCBG-f6Xfs5sk63mCfy0yxlIO7mW4Ja1AtUnP5nDy1dyN0alD0gnQg75GHTgzRI89c0Q9qfUCPPG5lsHxJ1DSnLbRRizbaQht1aKOINopooxZt1KKNWrRRjTa6Rxu1aHtFvn86u_zw2bN1OzyFHqDyIkh9SHkswlRnZxxHYYy-LOQqSMZRlnJk0ExlDGJsExlLsojzBHiWRL5-DD0KXpOjvMjhmFBgQZwIBSlTLEzTSawiHZgcx-BnkzQb9cnY_d9S2aT2urbKlXTRi0upbWSrrQYSbdQng2aftUnpcu-3mTOjtKTUkE2JqLt3v9MDmzen0lyRhZHokxMHAml76AYPgIRa4C_sk481LprdAF94CtjIrQxi7Cm4_oGL7oX4ttCbuKxxwc4iEbRyXq3e_OPVn5BH--79lhxV5TW8Iw_UtlpsylPbRX4Czs7hwg
linkProvider	Elsevier
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=An+approximate+dynamic+programming+approach+for+the+vehicle+routing+problem+with+stochastic+demands&rft.jtitle=European+journal+of+operational+research&rft.au=Novoa%2C+Clara&rft.au=Storer%2C+Robert&rft.date=2009-07-16&rft.pub=Elsevier+B.V&rft.issn=0377-2217&rft.eissn=1872-6860&rft.volume=196&rft.issue=2&rft.spage=509&rft.epage=515&rft_id=info:doi/10.1016%2Fj.ejor.2008.03.023&rft.externalDocID=S0377221708003172
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0377-2217&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0377-2217&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0377-2217&client=summon