*** Optimizing a multi-echelon location-inventory problem with joint replenishment: a Lipschitz ε-optimal approach using Lagrangian relaxation ***
Authors: Lin Wang, Sirui Wang, Lu Peng, and Yeming Gong
Corresponding author: Lu Peng
Contact Information: pengluhust@163.com 
  School of Management, Wuhan University of Technology, #122 Luoshi Rd., Wuhan, China 430070

***General Introduction***
This is the data repository for manuscript "optimizing a multi-echelon location-inventory 
problem with joint replenishment: a Lipschitz ε-optimal approach using Lagrangian relaxation".

It is being made public both to act as supplementary data for the manuscript submitted to 
International Journal of Production Research and in order for other researchers to use this 
data in their own work. The data repository contains all instances used in our study.

The dataset consists in two folders.
1) The inputData folder contains all orginal data of numerical instances,
2) The outputData folder contains the solutions of instances.

The data are all randomly generated and can be used publicly.


***Purpose of the experiments***
To test the performance of our algorithms.


***Test environment***
All experiments are programmed in MATLAB 2018b and implemented on a PC (CPU: 
Intel Core i5-8600K 3.6 GHz; RAM: 16 GB; OS: Windows 10). The facility location problem
is solved via calling Gurobi 9.0 in MATLAB.


***Description of the data in this data set***
Data of each  instance is stored in a single file. The naming obeys the camelcase rule, e.g., the file
"inputDataSize70n14m0.1s1times" means the input data of No.1 instance with n = 70, m = 14, and s = 0.1.
Variables naming follows the rule in our manuscript.