Dataset File
Description
"Set intended to study activity distribution morphology indicator influence. It is equilibrated on other morphologic indicators, and on resource indicators, and it have enough instances to allow obtain solid conclusions. See paper: Vanhoucke, Mario, Coelho, Jose. 2018. A tool to test and validate algorithms for the resource-constrained project scheduling problem, Computers & Industrial Engineering 118, 1: 251 - 265."
Number of instances
480000
Format
rcp+res
Statistics
Set statistics:
Number of instances: 480
- Solved (exact proc.): 355 (73.96%)
- Closed (LB=UB): 473 (98.54%)
- Open (LB<UB): 7 (1.46%)
Average deviation over CPM:
- Lower bound: 102.38%
- Upper bound: 102.43%
Sum of lower bounds: 51089
Sum of upper bounds: 51097
Open time units: 8 (0.02%)
Avg CPU lower bounds: 1152.795s (max 72000.280s)
Avg CPU upper bounds: 2.040s (max 60.300s)
Avg CPU optimal sol.: 0.198s (max 18.660s)
Reference 1:
- Lower bounds: 300 (62.50%)
- Upper bounds: 380 (79.17%)
- Optimal solutions: 354 (73.75%)
Reference 2:
- Lower bounds: 85 (17.71%)
Reference 4:
- Lower bounds: 41 (8.54%)
- Optimal solutions: 1 (0.21%)
Reference 3:
- Upper bounds: 20 (4.17%)
Number of instances: 480
- Solved (exact proc.): 355 (73.96%)
- Closed (LB=UB): 473 (98.54%)
- Open (LB<UB): 7 (1.46%)
Average deviation over CPM:
- Lower bound: 102.38%
- Upper bound: 102.43%
Sum of lower bounds: 51089
Sum of upper bounds: 51097
Open time units: 8 (0.02%)
Avg CPU lower bounds: 1152.795s (max 72000.280s)
Avg CPU upper bounds: 2.040s (max 60.300s)
Avg CPU optimal sol.: 0.198s (max 18.660s)
Reference 1:
- Lower bounds: 300 (62.50%)
- Upper bounds: 380 (79.17%)
- Optimal solutions: 354 (73.75%)
Reference 2:
- Lower bounds: 85 (17.71%)
Reference 4:
- Lower bounds: 41 (8.54%)
- Optimal solutions: 1 (0.21%)
Reference 3:
- Upper bounds: 20 (4.17%)
RecordSets
Record sets:
ID;1
Author(s); Demeulemeester, E. and Herroelen, W.
Reference; Demeulemeester, E. and Herroelen, W. (1992). A branch-and-bound procedure for the multiple resource-constrained project scheduling problem. Management Science, 38:1803-1818.
Date; 1992/01/01
Hardware / software; Stevin Supercomputer Infrastructure, C++, compiler intel/2017.02, Linux
Stop criteria; 1 second(s) / 60 second(s)
Submission date; 2017/5/26
ID;2
Author(s); Klein, R. and Scholl, A.
Reference;Klein, R. and Scholl, A. (1999). Computing lower bounds by destructive improvement: An application to resource-constrained project scheduling. European Journal of Operational Research, 112:322?346
Date; 1999/01/01
Hardware / software; i7, 16GB, 2GHz, C++, Visual Studio 2015 (x64), Windows 10
Stop criteria;none
Submission date; 2016/01/01
ID;3
Author(s); Debels, D. and Vanhoucke, M.
Reference; Debels, D. and Vanhoucke, M. (2007). A decomposition-based genetic algorithm for the resource-constrained project scheduling problems. Operations Research, 55:457-469.
Date; 2007/01/01
Hardware / software; Stevin Supercomputer Infrastructure, C++, compiler intel/2017.02, Linux
Stop criteria;cumulated results from several runs, on open instances only. Maximal run: 10 runs x 500k schedules
Submission date; 2017/5/21
ID;4
Author(s); Coelho, Jose and Vanhoucke, Mario
Reference; Coelho, Jose and Vanhoucke, Mario. 2019. Working paper 'Going to the core of hard resource-constrained project scheduling instances'
Date; 2019/08/01
Hardware / software; STEVIN HPC-UGent infrastructure, C++, compiler intel/2017.02, Linux
Stop criteria(s);Several procedures and stop criteria, the last one with 20 hours.
Submission date; 2020/03/01
ID;1
Author(s); Demeulemeester, E. and Herroelen, W.
Reference; Demeulemeester, E. and Herroelen, W. (1992). A branch-and-bound procedure for the multiple resource-constrained project scheduling problem. Management Science, 38:1803-1818.
Date; 1992/01/01
Hardware / software; Stevin Supercomputer Infrastructure, C++, compiler intel/2017.02, Linux
Stop criteria; 1 second(s) / 60 second(s)
Submission date; 2017/5/26
ID;2
Author(s); Klein, R. and Scholl, A.
Reference;Klein, R. and Scholl, A. (1999). Computing lower bounds by destructive improvement: An application to resource-constrained project scheduling. European Journal of Operational Research, 112:322?346
Date; 1999/01/01
Hardware / software; i7, 16GB, 2GHz, C++, Visual Studio 2015 (x64), Windows 10
Stop criteria;none
Submission date; 2016/01/01
ID;3
Author(s); Debels, D. and Vanhoucke, M.
Reference; Debels, D. and Vanhoucke, M. (2007). A decomposition-based genetic algorithm for the resource-constrained project scheduling problems. Operations Research, 55:457-469.
Date; 2007/01/01
Hardware / software; Stevin Supercomputer Infrastructure, C++, compiler intel/2017.02, Linux
Stop criteria;cumulated results from several runs, on open instances only. Maximal run: 10 runs x 500k schedules
Submission date; 2017/5/21
ID;4
Author(s); Coelho, Jose and Vanhoucke, Mario
Reference; Coelho, Jose and Vanhoucke, Mario. 2019. Working paper 'Going to the core of hard resource-constrained project scheduling instances'
Date; 2019/08/01
Hardware / software; STEVIN HPC-UGent infrastructure, C++, compiler intel/2017.02, Linux
Stop criteria(s);Several procedures and stop criteria, the last one with 20 hours.
Submission date; 2020/03/01
Relevant Results
Best Known Solutions
Original Instances
File Header
Title;Morphology AD indicator
Description;"Set intended to study activity distribution morphology indicator influence. It is equilibrated on other morphologic indicators, and on resource indicators, and it have enough instances to allow obtain solid conclusions. See paper: Vanhoucke, Mario, Coelho, Jose. 2018. A tool to test and validate algorithms for the resource-constrained project scheduling problem, Computers & Industrial Engineering 118, 1: 251 - 265."
Number;480000
Format;rcp+res
Description;"Set intended to study activity distribution morphology indicator influence. It is equilibrated on other morphologic indicators, and on resource indicators, and it have enough instances to allow obtain solid conclusions. See paper: Vanhoucke, Mario, Coelho, Jose. 2018. A tool to test and validate algorithms for the resource-constrained project scheduling problem, Computers & Industrial Engineering 118, 1: 251 - 265."
Number;480000
Format;rcp+res
Date