Data of the INFORMS Journal on Computing paper: Routing replenishment workers: The prize collecting traveling salesman problem in scattered storage warehouses

In what follows, you will find data of the paper:
"Routing replenishment workers: The prize collecting traveling salesman problem in scattered storage warehouses" published in INFORMS Journal on Computing

List of files:
- Computational_results_BB_NN_RW_CPLEX.xlsx: Excel file that gives all results
- instance_gen.cc: Instance generator
- instances.zip: compressed file of all instances that are sorted by Sections. It additionally includes the generator
- Makefile: Makefile for compiling/debugging, i.e., "make all" or "make debug" do the jobs
- MersenneTwister.h: needed by schedule_finder.cc
- results_Section_5_1.zip: compressed file of all output files of Section 5.1
- results_Section_5_2.zip: compressed file of all output files of Section 5.2
- results_Section_5_3.zip: compressed file of all output files of Section 5.3
- schedule_finder.cc: Main program containing the B&B, the S-shape, and Nearest Neighbor procedure (see details for customizing the parameters at the top of this file)
- valgrind_debug.txt: Only contains the used debug command

instances/instance_gen.cc generates a problem instance in file problems.txt
The structure of the these problem files is the following:
/*
NE                                              Total number of experiments given by the currently considered file
-2                                              Separator
EXPGRP                                          Index of the current experiment group the current experiment belong to
N                                               Number of vacant positions in the warehouse
M                                               Number of requests to be stored by the tour
P                                               Number of pickers to be scheduled in the warehouse
A                                               Number of vertical aisles
B                                               Number of horizontal (cross) aisles
L_A                                             Length of each vertical aisle
L_B                                             Length of each cross aisle
UF_VA                                           Up-factor of each vertical aisle (A values)
DF_VA                                           Down- factor of each vertical aisle (A values)
UF_CA                                           Up-factor of each cross aisle (B values)
DF_CA                                           Down- factor of each cross aisle (B values)
x_pos_vertical_aisle                            x-position of vertical aisle (A values)
y_pos_cross_aisle                               y-position of cross aisle (B values)
warehouse_graph values                          For each node of the warehouse graph all entries (15 each) are given (total_number_of_warehouse_graph_nodes*15)
   FS << warehouse_graph[curr_node].free_position << " " << endl;
   FS << warehouse_graph[curr_node].depot_node << " " << endl;
   FS << warehouse_graph[curr_node].vertical_aisle << " " << endl;
   FS << warehouse_graph[curr_node].cross_aisle << " " << endl;
   FS << warehouse_graph[curr_node].pred_cross_aisle << " " << endl;
   FS << warehouse_graph[curr_node].succ_cross_aisle << " " << endl;
   FS << warehouse_graph[curr_node].pred_vertical_aisle << " " << endl;
   FS << warehouse_graph[curr_node].succ_vertical_aisle << " " << endl;
   FS << warehouse_graph[curr_node].pred_cross_aisle_dist << " " << endl;
   FS << warehouse_graph[curr_node].succ_cross_aisle_dist << " " << endl;
   FS << warehouse_graph[curr_node].pred_vertical_aisle_dist << " " << endl;
   FS << warehouse_graph[curr_node].succ_vertical_aisle_dist << " " << endl;
   FS << warehouse_graph[curr_node].region << " " << endl;
   FS << warehouse_graph[curr_node].x_position << " " << endl;
   FS << warehouse_graph[curr_node].y_position << " " << endl;
shortest_path_distance                          For each combination of nodes (i.e., for total_number_of_warehouse_graph_nodes_square combinations) the distance
shortest_path_length_including_start_and_end    For each combination of nodes (i.e., for total_number_of_warehouse_graph_nodes_square combinations) the number of visited nodes
shortest_path_visited_nodes                     For each combination of nodes (i.e., for total_number_of_warehouse_graph_nodes_square combinations) the detailed path (length is respectively given by shortest_path_length_including_start_and_end)
dd_free_position                                For each free position and the depot (here with index N) the due date is transferred (N+1 values) (only relevant for the extended problem, is ignored here)
weight_of_free_position                         For each free position and the depot (here with index N) the weight is transferred (N+1 values) (only relevant for the extended problem, is ignored here)
capacity_of_free_position                       For each free position the storage capacity transferred (N values)
-2      Separator indicating the end of an instances
-3      Separator indicating the end of all experiments (i.e., indicating the end of the file)
*/

output files (results_Section_5_1.zip/results_Section_5_2.zip/results_Section_5_3.zip):
results_BB_NXXX_MYYY_A10_B05:  Output file of applying B&B
results_RW_NXXX_MYYY_A10_B05:  Output file of applying s-shape random walk
results_NN_NXXX_MYYY_A10_B05:  Output file of applying nearest neighbor

In these files you find all outputs of schedule_finder.cc.  
Among others, you will find the generated tour schedules (for Experiment with index I) in the output files by searching the phrase: "Experiment I completed with result="
or for the next Experiment " completed with result="

Example (results_BB_N030_M150_A10_B05.txt, experiment 0, the tardiness values are to be ignored, see comments in schedule_finder.cc)
Pos 0 depot node with index 80 Number of stored items 0 CT 0  No tardiness
Pos 1 position 27 Number of stored items 4 Current accumulated number of stored items 4 CT 163 DD 5629 No additional tardiness
Pos 2 position 28 Number of stored items 5 Current accumulated number of stored items 9 CT 399 DD 2962 No additional tardiness
Pos 3 position 29 Number of stored items 4 Current accumulated number of stored items 13 CT 670 DD 12631 No additional tardiness
Pos 4 position 26 Number of stored items 5 Current accumulated number of stored items 18 CT 840 DD 10142 No additional tardiness
Pos 5 position 23 Number of stored items 7 Current accumulated number of stored items 25 CT 1134 DD 6000 No additional tardiness
Pos 6 position 22 Number of stored items 4 Current accumulated number of stored items 29 CT 1170 DD 6396 No additional tardiness
Pos 7 position 16 Number of stored items 5 Current accumulated number of stored items 34 CT 1448 DD 8962 No additional tardiness
Pos 8 position 11 Number of stored items 10 Current accumulated number of stored items 44 CT 1674 DD 6336 No additional tardiness
Pos 9 position 0 Number of stored items 10 Current accumulated number of stored items 54 CT 2062 DD 1141 Additional tardiness 921
Pos 10 position 2 Number of stored items 9 Current accumulated number of stored items 63 CT 2201 DD 7742 No additional tardiness
Pos 11 position 4 Number of stored items 5 Current accumulated number of stored items 68 CT 2407 DD 4846 No additional tardiness
Pos 12 position 3 Number of stored items 5 Current accumulated number of stored items 73 CT 2717 DD 2316 Additional tardiness 401
Pos 13 position 1 Number of stored items 8 Current accumulated number of stored items 81 CT 2876 DD 9917 No additional tardiness
Pos 14 position 6 Number of stored items 3 Current accumulated number of stored items 84 CT 3073 DD 7299 No additional tardiness
Pos 15 position 5 Number of stored items 8 Current accumulated number of stored items 92 CT 3144 DD 6152 No additional tardiness
Pos 16 position 8 Number of stored items 6 Current accumulated number of stored items 98 CT 3337 DD 3705 No additional tardiness
Pos 17 position 12 Number of stored items 9 Current accumulated number of stored items 107 CT 3452 DD 7622 No additional tardiness
Pos 18 position 13 Number of stored items 4 Current accumulated number of stored items 111 CT 3522 DD 7833 No additional tardiness
Pos 19 position 14 Number of stored items 5 Current accumulated number of stored items 116 CT 3647 DD 9877 No additional tardiness
Pos 20 position 19 Number of stored items 1 Current accumulated number of stored items 117 CT 3922 DD 2905 Additional tardiness 1017
Pos 21 position 20 Number of stored items 5 Current accumulated number of stored items 122 CT 3923 DD 2538 Additional tardiness 1385
Pos 22 position 21 Number of stored items 7 Current accumulated number of stored items 129 CT 3976 DD 2769 Additional tardiness 1207
Pos 23 position 18 Number of stored items 10 Current accumulated number of stored items 139 CT 4173 DD 3552 Additional tardiness 621
Pos 24 position 25 Number of stored items 4 Current accumulated number of stored items 143 CT 4482 DD 11710 No additional tardiness
Pos 25 position 24 Number of stored items 7 Current accumulated number of stored items 150 CT 4509 DD 10599 No additional tardiness
Pos 26 visiting the node with index 80 Number of stored items 0 CT 4710 DD 10893 No additional tardiness
opt_makespan=4710 opt_total_tardiness=5552
TSP_procedure returned value 4710
Experiment 0 completed with result=3
BFS Branch&Bound report: Consumed time: 1

Copied from schedule_finder.cc:
Note that the procedure used as a solution procedure in the paper is int TSP_procedure(struct bb_node *curr_bb_node, int version)

It is called by BB_procedure() as a subroutine for computing a lower bound value of an extended problem
(for instance, this extended problem additionally covers due dates. Therefore, due dates are also part of the problem instances, but can be ignored)
Specifically, TSP_procedure(struct bb_node *curr_bb_node, int version) is called once by lb_computation()