This "readme" file explains the naming and file format for the instance files provided in this repository.

If using these instances, please consider citing the paper:
A. Wang, X. Li, J.E. Arbogast, G. Bonnier, Z. Wilson and C.E. Gounaris (2025),
"A Novel Mixed-Integer Linear Programming Formulation for Continuous-Time Inventory Routing"
Computers & Operations Research, 174:106883. DOI 10.1016/j.cor.2024.106883

These benchmarks were adapted from the ROADEF/EURO Challenge 2016 competition https://www.roadef.org/challenge/2016/en/index.php. 

The naming "RF-X-nY-kZ" signifies that the X-th original instance (version 1.1 "set A" dataset) was adapted to include Y customers and Z vehicles.

Below, we utilize instance 'RF-3-n5-k1' as an example to show how each file provides the details of each benchmark.

########################################################
## instance name
INSTANCE: RF-3-n5-k1


## planning horizon      
Time H: 168


## number of vehicles
N VEHICLES: 1


## vehicle capacity
CAP Q: 800


## initial, final, minimum and maximum inventory, as well as constant consumption rate (USAGE), associated with each node (where node '0' is the depot).
NODE    INITIAL      FINAL        MIN        MAX      USAGE 
  0          0          0          0          0       0.00 
  1       1109       1109        488       4885       1.73 
  2        483        483        156        782       0.40 
  3       2043       2043        293       4885      11.20 
  4       2770       2770       2067       3180       0.74 
  5       8478       8478       2214      11070      24.16 


## travel time matrix  
TRAVEL TIME
   0.00   3.31   3.38   3.35   3.32   3.48
   1.31   0.00   2.95   0.81   0.79   0.98
   1.38   3.03   0.00   3.08   3.05   3.13
   1.35   0.85   3.03   0.00   0.80   1.00
   1.32   0.81   2.98   0.78   0.00   0.97
   1.40   0.88   2.97   0.90   0.88   0.00


## travel cost matrix   
TRAVEL COST
    0.0   53.9   55.3   56.0   54.6   57.4
   53.9    0.0   81.9    5.6    2.8    9.8
   56.0  100.1    0.0  101.5   98.7   99.4
   56.0    9.1   88.2    0.0    4.9   14.7
   54.6    4.9   84.7    3.5    0.0   12.6
   57.4   10.5   83.3   14.0   11.2    0.0
##########################################################