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Analysis of institutional authors

Garcia Pardo, EduardoAuthorGil-Borras, SergioAuthor

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August 31, 2020
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Fixed versus variable time window warehousing strategies in real time

Publicated to: Progress in artificial intelligence. 9 (4): 315-324 - 2020-12-01 9(4), DOI: 10.1007/s13748-020-00215-1

Authors:

Gil-Borras, Sergio; Pardo, Eduardo G; Alonso-Ayuso, Antonio; Duarte, Abraham
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Affiliations

Univ Politecn Madrid, Dept Sistemas Informat, Madrid, Spain - Author
Univ Rey Juan Carlos, Dept Comp Sci, Mostoles, Spain - Author

Abstract

Warehousing includes many different regular activities such as receiving, batching, picking, packaging, and shipping goods. Several authors indicate that the picking operation might consume up to 55% of the total operational costs. In this paper, we deal with a subtask arising within the picking task in a warehouse, when the picking policy follows the order batching strategy (i.e., orders are grouped into batches before being collected) and orders are received online. Particularly, once the batches have been compiled it is necessary to determine the moment in the time when the picker starts collecting each batch. The waiting time of the picker before starting to collect the next available batch is usually known as time window. In this paper, we compare the performance of two different time window strategies: Fixed Time Window and Variable Time Window. Since those strategies cannot be tested in isolation, we have considered: two different batching algorithms (First Come First Served and a Greedy algorithm based on weight); one routing algorithm (S-Shape); and a greedy selection algorithm for choosing the next batch to collect based on the weight.
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Keywords

AssignmentFixed time windowMilp formulationsMultiple pickersNeighborhood searchOnline order batchingOrder batching problemPickingTime windowVariable time windowWarehousing

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Progress in artificial intelligence, Q3 Agency Scopus (SJR), its regional focus and specialization in Artificial Intelligence, give it significant recognition in a specific niche of scientific knowledge at an international level.

Independientemente del impacto esperado determinado por el canal de difusión, es importante destacar el impacto real observado de la propia aportación.

Según las diferentes agencias de indexación, el número de citas acumuladas por esta publicación hasta la fecha 2026-04-27:

  • WoS: 6
  • Scopus: 8
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Impact and social visibility

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

  • Assignment of a Handle/URN as an identifier within the deposit in the Institutional Repository: https://oa.upm.es/86616/

As a result of the publication of the work in the institutional repository, statistical usage data has been obtained that reflects its impact. In terms of dissemination, we can state that, as of

  • Views: 166
  • Downloads: 1
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Leadership analysis of institutional authors

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (GIL BORRAS, SERGIO) .

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Awards linked to the item

This research was partially funded by the projects: RTI2018-094269-B-I00 and PGC2018-095322-B-C22 from Ministerio de Ciencia, Innovacion y Universidades (Spain); by Comunidad de Madrid and European Regional Development Fund, Grant Ref. P2018/TCS-4566; and by Programa Propio de I+D+i de la Universidad Politecnica de Madrid (Programa 466A).
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