Dataset for "Inventory Routing in a Warehouse: The Storage Replenishment Routing Problem"

This dataset relates to testing of a heuristic approach using operational research techniques for a specific routing problem in a warehouse, defined as the Storage Replenishment Routing Problem. There are a total of 620 instances, stored as .dat or .txt files, classified into two groups depending on the sizes of the instances. The 300 smaller instances consist of different settings ranging from 25 to 150 pick items and from 3 to 15 replenishment periods. Each setting consists of 10 instances randomly generated by changing the items to be picked in the warehouse, their locations in the warehouse, initial inventory levels, and maximum storage capacities in the forward storage area. The 320 larger instances involve 450 pick items and 15 replenishment periods, with each setting including 10 random instances generated by changing the items to be picked in the warehouse, their locations in the warehouse, initial inventory levels, maximum storage capacities in the forward storage area, and the skewness of the demand (ranging from uniform to 20-80 skewness).

To use any of the instances, the user needs to read the data given in the corresponding text file into the optimisation software or the platform where their heuristic is coded in.

The target audience for this dataset is operational researchers working on developing heuristic approaches for similar routing problems in warehouses.

Keywords:
Routing, Warehouse management, Storage replenishment, Order picking, Inventory routing, Heuristics
Subjects:
Management and Business studies
Mathematical sciences

Cite this dataset as:
Celik, M., Archetti, C., Sural, H., 2021. Dataset for "Inventory Routing in a Warehouse: The Storage Replenishment Routing Problem". Bath: University of Bath Research Data Archive. Available from: https://doi.org/10.15125/BATH-00976.

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Data

SRRP-instances.zip
application/zip (13MB)
Creative Commons: Attribution 4.0

The document is a compressed file that includes two folders including two different instance sets for the Storage Replenishment Routing Problem, differing in their size. Each instance is stored as a .dat or .txt file, which can be read as input data in any optimisation software or any programming language.

Creators

Melih Celik
University of Bath

Claudia Archetti
ESSEC Business School

Haldun Sural
Middle East Technical University

Contributors

University of Bath
Rights Holder

Documentation

Data collection method:

The data has been generated using warehouse parameters from "Roodbergen, K.J. and de Koster, R.B.M. (2001). Routing methods for warehouses with multiple cross aisles. International Journal of Production Research, 39(9): 1865-1883." and using the inventory routing parameters from "Solyali, O. and Sural, H. (2011). A Branch-and-Cut Algorithm Using a Strong Formulation and an A Priori Tour-Based Heuristic for an Inventory-Routing Problem. Transportation Science, 45(3): 335-345." Each instance setting consists of 10 instances, randomly generating the picking demand, maximum inventory levels and initial inventories.

Data processing and preparation activities:

No third-party datasets were directly used, but the methodology used in two different papers were replicated. Please see Data Collection Method for sources.

Technical details and requirements:

The data has been generated using a random instance generator coded in C++ using Microsoft Visual Studio 2019.

Funders

Self-funded

Publication details

Publication date: 7 December 2021
by: University of Bath

Version: 1

DOI: https://doi.org/10.15125/BATH-00976

URL for this record: https://researchdata.bath.ac.uk/id/eprint/976

Related papers and books

Çelik, M., Archetti, C. and Süral, H., 2021. Inventory routing in a warehouse: The storage replenishment routing problem. European Journal of Operational Research. Available from: https://doi.org/10.1016/j.ejor.2021.11.056.

Contact information

Please contact the Research Data Service in the first instance for all matters concerning this item.

Contact person: Melih Celik

Departments:

School of Management
Information, Decisions & Operations