A biased-randomized iterated local search for the vehicle routing problem with optional backhauls
The vehicle routing problem with backhauls integrates decisions on product delivery with decisions on the collection of returnable items. In this paper, we analyze a scenario in which collection of items is optional—but subject to a penalty cost. Both transportation costs and penalties associated wi...
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Published in | TOP Vol. 29; no. 2; pp. 387 - 416 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Berlin/Heidelberg
Springer Berlin Heidelberg
01.07.2021
Springer Nature B.V |
Subjects | |
Online Access | Get full text |
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Summary: | The vehicle routing problem with backhauls integrates decisions on product delivery with decisions on the collection of returnable items. In this paper, we analyze a scenario in which collection of items is optional—but subject to a penalty cost. Both transportation costs and penalties associated with non-collecting decisions are considered. A mixed-integer linear model is proposed and solved for small instances. Also, a metaheuristic algorithm combining biased randomization techniques with iterated local search is introduced for larger instances. Our approach yields cost savings and is competitive when compared to other state-of-the-art approaches. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
ISSN: | 1134-5764 1863-8279 |
DOI: | 10.1007/s11750-020-00558-x |