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GRASP with Variable Neighborhood Descent for the online order batching problem

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Abstract

The Online Order Batching Problem (OOBP) is a variant of the well-known Order Batching Problem (OBP). As in the OBP, the goal of this problem is to collect all the orders that arrive at a warehouse, following an order batching picking policy, while minimizing a particular objective function. Therefore, orders are grouped in batches, of a maximum predefined capacity, before being collected. Each batch is assigned to a single picker, who collects all the orders within the batch in a single route. Unlike the OBP, this variant presents the peculiarity that the orders considered in each instance are not fully available in the warehouse at the beginning of the day, but they can arrive at the system once the picking process has already begun. Then, batches have to be dynamically updated and, as a consequence, routes must too. In this paper, the maximum turnover time (maximum time that an order remains in the warehouse) and the maximum completion time (total collecting time of all orders received in the warehouse) are minimized. To that aim, we propose an algorithm based in the combination of a Greedy Randomized Adaptive Search Procedure and a Variable Neighborhood Descent. The best variant of our method has been tested over a large set of instances and it has been favorably compared with the best previous approach in the state of the art.

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Author information

Authors and Affiliations

  1. Universidad Politécnica de Madrid, C/Alan Turing s/n (Ctra. de Valencia, Km. 7), 28031, Madrid, Spain

    Sergio Gil-Borrás

  2. Universidad Rey Juan Carlos, C/Tulipán s/n, 28933, Móstoles, Madrid, Spain

    Eduardo G. Pardo, Antonio Alonso-Ayuso & Abraham Duarte

Authors
  1. Sergio Gil-Borrás
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  2. Eduardo G. Pardo
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  3. Antonio Alonso-Ayuso
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  4. Abraham Duarte
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Corresponding author

Correspondence to Eduardo G. Pardo.

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This research was partially funded by the projects: MTM2015-63710-P, RTI2018-094269-B-I00, TIN2015-65460-C2-2-P and PGC2018-095322-B-C22 from Ministerio de Ciencia, Innovación 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 Politécnica de Madrid (Programa 466A).

Appendices

Appendix A: Results per instance (instance set Albareda [1])

Table 13 Results per instance for the dataset introduced in [1] over the two considered objective functions
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Appendix B: Results per instance (instance set Henn [18])

Table 14 Results per instance for the dataset introduced in [18] over the two considered objective functions
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Gil-Borrás, S., Pardo, E.G., Alonso-Ayuso, A. et al. GRASP with Variable Neighborhood Descent for the online order batching problem. J Glob Optim 78, 295–325 (2020). https://doi.org/10.1007/s10898-020-00910-2

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