Improved solutions to dynamic and stochastic maritime pick-up and delivery problems using local search
Abstract Heuristics for stochastic and dynamic vehicle routing problems are often kept relatively simple, in part due to the high computational burden resulting from having to consider stochastic information in some form. In this work, three existing heuristics are extended by three different local...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Tirado, Gregorio [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2016 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer Science+Business Media New York 2016 |
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| Übergeordnetes Werk: |
Enthalten in: Annals of operations research - Springer US, 1984, 253(2016), 2 vom: 02. Apr., Seite 825-843 |
|---|---|
| Übergeordnetes Werk: |
volume:253 ; year:2016 ; number:2 ; day:02 ; month:04 ; pages:825-843 |
| Links: |
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| DOI / URN: |
10.1007/s10479-016-2177-5 |
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OLC2111176982 |
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| 520 | |a Abstract Heuristics for stochastic and dynamic vehicle routing problems are often kept relatively simple, in part due to the high computational burden resulting from having to consider stochastic information in some form. In this work, three existing heuristics are extended by three different local search variations: a first improvement descent using stochastic information, a tabu search using stochastic information when updating the incumbent solution, and a tabu search using stochastic information when selecting moves based on a list of moves determined through a proxy evaluation. In particular, the three local search variations are designed to utilize stochastic information in the form of sampled scenarios. The results indicate that adding local search using stochastic information to the existing heuristics can further reduce operating costs for shipping companies by 0.5–2 %. While the existing heuristics could produce structurally different solutions even when using similar stochastic information in the search, the appended local search methods seem able to make the final solutions more similar in structure. | ||
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10.1007/s10479-016-2177-5 doi (DE-627)OLC2111176982 (DE-He213)s10479-016-2177-5-p DE-627 ger DE-627 rakwb eng 004 VZ 3,2 ssgn Tirado, Gregorio verfasserin aut Improved solutions to dynamic and stochastic maritime pick-up and delivery problems using local search 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media New York 2016 Abstract Heuristics for stochastic and dynamic vehicle routing problems are often kept relatively simple, in part due to the high computational burden resulting from having to consider stochastic information in some form. In this work, three existing heuristics are extended by three different local search variations: a first improvement descent using stochastic information, a tabu search using stochastic information when updating the incumbent solution, and a tabu search using stochastic information when selecting moves based on a list of moves determined through a proxy evaluation. In particular, the three local search variations are designed to utilize stochastic information in the form of sampled scenarios. The results indicate that adding local search using stochastic information to the existing heuristics can further reduce operating costs for shipping companies by 0.5–2 %. While the existing heuristics could produce structurally different solutions even when using similar stochastic information in the search, the appended local search methods seem able to make the final solutions more similar in structure. Tabu search Uncertainty Scenario Routing Hvattum, Lars Magnus aut Enthalten in Annals of operations research Springer US, 1984 253(2016), 2 vom: 02. Apr., Seite 825-843 (DE-627)12964370X (DE-600)252629-3 (DE-576)018141862 0254-5330 volume:253 year:2016 number:2 day:02 month:04 pages:825-843 https://doi.org/10.1007/s10479-016-2177-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-WIW SSG-OLC-MAT AR 253 2016 2 02 04 825-843 |
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10.1007/s10479-016-2177-5 doi (DE-627)OLC2111176982 (DE-He213)s10479-016-2177-5-p DE-627 ger DE-627 rakwb eng 004 VZ 3,2 ssgn Tirado, Gregorio verfasserin aut Improved solutions to dynamic and stochastic maritime pick-up and delivery problems using local search 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media New York 2016 Abstract Heuristics for stochastic and dynamic vehicle routing problems are often kept relatively simple, in part due to the high computational burden resulting from having to consider stochastic information in some form. In this work, three existing heuristics are extended by three different local search variations: a first improvement descent using stochastic information, a tabu search using stochastic information when updating the incumbent solution, and a tabu search using stochastic information when selecting moves based on a list of moves determined through a proxy evaluation. In particular, the three local search variations are designed to utilize stochastic information in the form of sampled scenarios. The results indicate that adding local search using stochastic information to the existing heuristics can further reduce operating costs for shipping companies by 0.5–2 %. While the existing heuristics could produce structurally different solutions even when using similar stochastic information in the search, the appended local search methods seem able to make the final solutions more similar in structure. Tabu search Uncertainty Scenario Routing Hvattum, Lars Magnus aut Enthalten in Annals of operations research Springer US, 1984 253(2016), 2 vom: 02. Apr., Seite 825-843 (DE-627)12964370X (DE-600)252629-3 (DE-576)018141862 0254-5330 volume:253 year:2016 number:2 day:02 month:04 pages:825-843 https://doi.org/10.1007/s10479-016-2177-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-WIW SSG-OLC-MAT AR 253 2016 2 02 04 825-843 |
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Abstract Heuristics for stochastic and dynamic vehicle routing problems are often kept relatively simple, in part due to the high computational burden resulting from having to consider stochastic information in some form. In this work, three existing heuristics are extended by three different local search variations: a first improvement descent using stochastic information, a tabu search using stochastic information when updating the incumbent solution, and a tabu search using stochastic information when selecting moves based on a list of moves determined through a proxy evaluation. In particular, the three local search variations are designed to utilize stochastic information in the form of sampled scenarios. The results indicate that adding local search using stochastic information to the existing heuristics can further reduce operating costs for shipping companies by 0.5–2 %. While the existing heuristics could produce structurally different solutions even when using similar stochastic information in the search, the appended local search methods seem able to make the final solutions more similar in structure. © Springer Science+Business Media New York 2016 |
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Abstract Heuristics for stochastic and dynamic vehicle routing problems are often kept relatively simple, in part due to the high computational burden resulting from having to consider stochastic information in some form. In this work, three existing heuristics are extended by three different local search variations: a first improvement descent using stochastic information, a tabu search using stochastic information when updating the incumbent solution, and a tabu search using stochastic information when selecting moves based on a list of moves determined through a proxy evaluation. In particular, the three local search variations are designed to utilize stochastic information in the form of sampled scenarios. The results indicate that adding local search using stochastic information to the existing heuristics can further reduce operating costs for shipping companies by 0.5–2 %. While the existing heuristics could produce structurally different solutions even when using similar stochastic information in the search, the appended local search methods seem able to make the final solutions more similar in structure. © Springer Science+Business Media New York 2016 |
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Abstract Heuristics for stochastic and dynamic vehicle routing problems are often kept relatively simple, in part due to the high computational burden resulting from having to consider stochastic information in some form. In this work, three existing heuristics are extended by three different local search variations: a first improvement descent using stochastic information, a tabu search using stochastic information when updating the incumbent solution, and a tabu search using stochastic information when selecting moves based on a list of moves determined through a proxy evaluation. In particular, the three local search variations are designed to utilize stochastic information in the form of sampled scenarios. The results indicate that adding local search using stochastic information to the existing heuristics can further reduce operating costs for shipping companies by 0.5–2 %. While the existing heuristics could produce structurally different solutions even when using similar stochastic information in the search, the appended local search methods seem able to make the final solutions more similar in structure. © Springer Science+Business Media New York 2016 |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">OLC2111176982</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230502202851.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">230502s2016 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s10479-016-2177-5</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC2111176982</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-He213)s10479-016-2177-5-p</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">004</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">3,2</subfield><subfield code="2">ssgn</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Tirado, Gregorio</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Improved solutions to dynamic and stochastic maritime pick-up and delivery problems using local search</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2016</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer Science+Business Media New York 2016</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Heuristics for stochastic and dynamic vehicle routing problems are often kept relatively simple, in part due to the high computational burden resulting from having to consider stochastic information in some form. In this work, three existing heuristics are extended by three different local search variations: a first improvement descent using stochastic information, a tabu search using stochastic information when updating the incumbent solution, and a tabu search using stochastic information when selecting moves based on a list of moves determined through a proxy evaluation. In particular, the three local search variations are designed to utilize stochastic information in the form of sampled scenarios. The results indicate that adding local search using stochastic information to the existing heuristics can further reduce operating costs for shipping companies by 0.5–2 %. 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