Heuristic, meta-heuristic and hyper-heuristic approaches for fresh produce inventory control and shelf space allocation.
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| Title: | Heuristic, meta-heuristic and hyper-heuristic approaches for fresh produce inventory control and shelf space allocation. |
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| Authors: | Bai, R.1 rzb@cs.nott.ac.uk, Burke, E. K.1, Kendall, G.1 |
| Source: | Journal of the Operational Research Society. Oct2008, Vol. 59 Issue 10, p1387-1397. 11p. 3 Charts, 6 Graphs. |
| Subjects: | Fresh food manufacturing, Food production, Decision making, Customer services, Tesco PLC, Algorithms, Simulated annealing |
| Abstract: | The allocation of fresh produce to shelf space represents a new decision support research area which is motivated by the desire of many retailers to improve their service due to the increasing demand for fresh food. However, automated decision making for fresh produce allocation is challenging because of the very short lifetime of fresh products. This paper considers a recently proposed practical model for the problem which is motivated by our collaboration with Tesco. Moreover, the paper investigates heuristic and meta-heuristic approaches as alternatives for the generalized reduced gradient algorithm, which becomes inefficient when the problem size becomes larger. A simpler single-item inventory problem is firstly studied and solved by a polynomial time bounded procedure. Several dynamic greedy heuristics are then developed for the multi-item problem based on the procedure for the single-item inventory problem. Experimental results show that these greedy heuristics are much more efficient and provide competitive results when compared to those of a multi-start generalized reduced gradient algorithm. In order to further improve the solution, we investigated simulated annealing, a greedy randomized adaptive search procedure and three types of hyper-heuristics. Their performance is tested and compared on a set of problem instances which are made publicly available for the research community. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of the Operational Research Society is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 34491761 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Heuristic, meta-heuristic and hyper-heuristic approaches for fresh produce inventory control and shelf space allocation. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Bai%2C+R%2E%22">Bai, R.</searchLink><relatesTo>1</relatesTo><i> rzb@cs.nott.ac.uk</i><br /><searchLink fieldCode="AR" term="%22Burke%2C+E%2E+K%2E%22">Burke, E. K.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Kendall%2C+G%2E%22">Kendall, G.</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+the+Operational+Research+Society%22">Journal of the Operational Research Society</searchLink>. Oct2008, Vol. 59 Issue 10, p1387-1397. 11p. 3 Charts, 6 Graphs. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Fresh+food+manufacturing%22">Fresh food manufacturing</searchLink><br /><searchLink fieldCode="DE" term="%22Food+production%22">Food production</searchLink><br /><searchLink fieldCode="DE" term="%22Decision+making%22">Decision making</searchLink><br /><searchLink fieldCode="DE" term="%22Customer+services%22">Customer services</searchLink><br /><searchLink fieldCode="DE" term="%22Tesco+PLC%22">Tesco PLC</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Simulated+annealing%22">Simulated annealing</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The allocation of fresh produce to shelf space represents a new decision support research area which is motivated by the desire of many retailers to improve their service due to the increasing demand for fresh food. However, automated decision making for fresh produce allocation is challenging because of the very short lifetime of fresh products. This paper considers a recently proposed practical model for the problem which is motivated by our collaboration with Tesco. Moreover, the paper investigates heuristic and meta-heuristic approaches as alternatives for the generalized reduced gradient algorithm, which becomes inefficient when the problem size becomes larger. A simpler single-item inventory problem is firstly studied and solved by a polynomial time bounded procedure. Several dynamic greedy heuristics are then developed for the multi-item problem based on the procedure for the single-item inventory problem. Experimental results show that these greedy heuristics are much more efficient and provide competitive results when compared to those of a multi-start generalized reduced gradient algorithm. In order to further improve the solution, we investigated simulated annealing, a greedy randomized adaptive search procedure and three types of hyper-heuristics. Their performance is tested and compared on a set of problem instances which are made publicly available for the research community. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Journal of the Operational Research Society is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1057/palgrave.jors.2602463 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 11 StartPage: 1387 Subjects: – SubjectFull: Fresh food manufacturing Type: general – SubjectFull: Food production Type: general – SubjectFull: Decision making Type: general – SubjectFull: Customer services Type: general – SubjectFull: Tesco PLC Type: general – SubjectFull: Algorithms Type: general – SubjectFull: Simulated annealing Type: general Titles: – TitleFull: Heuristic, meta-heuristic and hyper-heuristic approaches for fresh produce inventory control and shelf space allocation. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Bai, R. – PersonEntity: Name: NameFull: Burke, E. K. – PersonEntity: Name: NameFull: Kendall, G. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 10 Text: Oct2008 Type: published Y: 2008 Identifiers: – Type: issn-print Value: 01605682 Numbering: – Type: volume Value: 59 – Type: issue Value: 10 Titles: – TitleFull: Journal of the Operational Research Society Type: main |
| ResultId | 1 |
