976 32 14548 4 45096 document 14548 SRRP-instances.zip application/zip e4e97540c2741b5fe151dfa2473b0062 MD5 13632574 2021-02-22 14:09:09 https://researchdata.bath.ac.uk/976/1/SRRP-instances.zip 976 1 1 application/zip other 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. en public cc_by

SRRP-instances.zip

data archive 10118 disk0/00/00/09/76 2021-12-22 11:27:26 2024-05-14 13:12:14 2021-12-22 11:27:26 data_collection show Celik Melih M.Celik@bath.ac.uk 0000-0002-4694-3763 University of Bath TRUE Archetti Claudia archetti@essec.edu ESSEC Business School FALSE Sural Haldun hsural@metu.edu.tr Middle East Technical University FALSE FS0040 GJ0050 dept_ido Routing, Warehouse management, Storage replenishment, Order picking, Inventory routing, Heuristics 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. 2021-12-07 University of Bath public RightsHolder University of Bath Self-funded 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. No third-party datasets were directly used, but the methodology used in two different papers were replicated. Please see Data Collection Method for sources. The data has been generated using a random instance generator coded in C++ using Microsoft Visual Studio 2019. en 1 10.15125/BATH-00976 https://doi.org/10.1016/j.ejor.2021.11.056 pub open