Dataset File
Description
Dataset proposed in the paper Kolisch, R., & Sprecher, A. (1997). PSPLIB - A project scheduling problem library. European Journal of Operational Research, 96(1), 205-216. https://doi.org/10.1016/S0377-2217(96)00170-1
Number of instances
480
Format
sm
Statistics
Set statistics:
Number of instances: 480
- Solved (exact proc.): 412 (85.83%)
- Closed (LB=UB): 414 (86.25%)
- Open (LB<UB): 66 (13.75%)
Average deviation over CPM:
- Lower bound: 8.53%
- Upper bound: 9.42%
Sum of lower bounds: 45179
Sum of upper bounds: 45548
Open time units: 369 (0.82%)
Avg CPU lower bounds: 249.967s (max 23852.000s)
Avg CPU upper bounds: 20.128s (max 3600.010s)
Avg CPU optimal sol.: 177.787s (max 23852.000s)
Reference 7:
- Lower bounds: 17 (3.54%)
- Upper bounds: 15 (3.12%)
- Optimal solutions: 20 (4.17%)
Reference 2:
- Lower bounds: 5 (1.04%)
Reference 1:
- Lower bounds: 17 (3.54%)
- Upper bounds: 353 (73.54%)
- Optimal solutions: 344 (71.67%)
Reference 10:
- Lower bounds: 28 (5.83%)
- Upper bounds: 9 (1.88%)
- Optimal solutions: 14 (2.92%)
Reference 3:
- Upper bounds: 92 (19.17%)
Reference 4:
- Lower bounds: 18 (3.75%)
- Upper bounds: 3 (0.62%)
- Optimal solutions: 18 (3.75%)
Reference 5:
- Lower bounds: 10 (2.08%)
- Upper bounds: 1 (0.21%)
- Optimal solutions: 10 (2.08%)
Reference 9:
- Lower bounds: 33 (6.88%)
Reference 11:
- Lower bounds: 14 (2.92%)
- Upper bounds: 4 (0.83%)
- Optimal solutions: 6 (1.25%)
Reference 8:
- Upper bounds: 3 (0.62%)
Reference 6:
- Lower bounds: 1 (0.21%)
Number of instances: 480
- Solved (exact proc.): 412 (85.83%)
- Closed (LB=UB): 414 (86.25%)
- Open (LB<UB): 66 (13.75%)
Average deviation over CPM:
- Lower bound: 8.53%
- Upper bound: 9.42%
Sum of lower bounds: 45179
Sum of upper bounds: 45548
Open time units: 369 (0.82%)
Avg CPU lower bounds: 249.967s (max 23852.000s)
Avg CPU upper bounds: 20.128s (max 3600.010s)
Avg CPU optimal sol.: 177.787s (max 23852.000s)
Reference 7:
- Lower bounds: 17 (3.54%)
- Upper bounds: 15 (3.12%)
- Optimal solutions: 20 (4.17%)
Reference 2:
- Lower bounds: 5 (1.04%)
Reference 1:
- Lower bounds: 17 (3.54%)
- Upper bounds: 353 (73.54%)
- Optimal solutions: 344 (71.67%)
Reference 10:
- Lower bounds: 28 (5.83%)
- Upper bounds: 9 (1.88%)
- Optimal solutions: 14 (2.92%)
Reference 3:
- Upper bounds: 92 (19.17%)
Reference 4:
- Lower bounds: 18 (3.75%)
- Upper bounds: 3 (0.62%)
- Optimal solutions: 18 (3.75%)
Reference 5:
- Lower bounds: 10 (2.08%)
- Upper bounds: 1 (0.21%)
- Optimal solutions: 10 (2.08%)
Reference 9:
- Lower bounds: 33 (6.88%)
Reference 11:
- Lower bounds: 14 (2.92%)
- Upper bounds: 4 (0.83%)
- Optimal solutions: 6 (1.25%)
Reference 8:
- Upper bounds: 3 (0.62%)
Reference 6:
- Lower bounds: 1 (0.21%)
RecordSets
Record sets:
ID;1
Author(s); Demeulemeester, E. and Herroelen, W.
Reference;Demeulemeester, E., & Herroelen, W. (1992). A Branch-and-Bound Procedure for the Multiple Resource-Constrained Project Scheduling Problem. Management Science, 38(12), 1803-1818. http://www.jstor.org/stable/2632711
Date; 1992/01/01
Hardware / software; i7, 16GB, 2GHz, C++, Visual Studio 2015 (x64), Windows 10
Stop criteria;1m and 1h runs
Submission date; 2016/01/01
ID;2
Author(s); Klein, R. and Scholl, A.
Reference;Klein, R., & Scholl, A. (1999). Computing lower bounds by destructive improvement: An application to resource-constrained project scheduling. European Journal of Operational Research, 112(2), 322-346. https://doi.org/10.1016/S0377-2217(97)00442-6
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., & Vanhoucke, M. (2007). A Decomposition-Based Genetic Algorithm for the Resource-Constrained Project-Scheduling Problem. Operations Research, 55(3), 457-469. https://doi.org/10.1287/opre.1060.0358
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: 1000 runs x 500k schedules
Submission date; 2017/5/21
ID;4
Author(s); Andrei Horbach
Reference;Horbach, A. (2010). A Boolean satisfiability approach to the resource-constrained project scheduling problem. Annals of Operations Research, 181(1), 89–107. https://doi.org/10.1007/s10479-010-0693-2
Date;05/02/2010
Hardware / software;Dell Precision with Intel Core2Duo T6400 2.2GHz with 1 GB of RAM running under Windows XP (data extracted from table 5 and 6 in the paper)
Stop criteria(s);Maximal time 20 hours
Submission date;2024
ID;5
Author(s);Schutt, A., Feydy, T., Stuckey, P.J., Wallace, M.G.
Reference;Schutt, A., Feydy, T., Stuckey, P. J., & Wallace, M. G. (2011). Explaining the cumulative propagator. Constraints, 16(3), 250-282. https://doi.org/10.1007/s10601-010-9103-2
Date; 2011/07/01
Hardware / software;X86-64 architecture running GNU/Linux and a Intel(R) Xeon(R) CPU E54052 processor with 2 GHz. Code in Mercury using the G12 Constraint Programming Platform
Stop criteria(s);10 min, results reported in the paper as new results at the time of publication
Submission date; 2019/10/28
ID;6
Author(s);Petr Vilim
Reference;Vilim, P. (2011). Timetable Edge Finding Filtering Algorithm for Discrete Cumulative Resources. International Conference on AI and OR Techniques in Constriant Programming for Combinatorial Optimization Problems, 16. https://doi.org/10.1007/978-3-642-21311-3_22
Date;2011
Hardware / software;Intel(R) Core(TM)2 Duo CPU T9400 on 2.53GHz
Stop criteria;time limit for each improvement step is 60 seconds
Submission date;2021
ID;7
Author(s); Coelho, J. and Vanhoucke, M.
Reference;Coelho, J., & Vanhoucke, M. (2018). An exact composite lower bound strategy for the resource-constrained project scheduling problem. Computers & Operations Research, 93, 135-150. https://doi.org/10.1016/j.cor.2018.01.017
Date; 2017/06/01
Hardware / software; STEVIN HPC-UGent infrastructure, C++, compiler intel/2017.02, Linux
Stop criteria(s);Best results from all runs, with maximal run time of 1h
Submission date; 2017/12/31
ID;8
Author(s);Vanhoucke, M. and Coelho, J.
Reference;Vanhoucke, M., & Coelho, J. (2024). A matheuristic for the resource-constrained project scheduling problem. European Journal of Operational Research, 319(3), 711725. https://doi.org/10.1016/j.ejor.2024.07.016
Date;01/12/2024
Hardware / software; STEVIN HPC-UGent infrastructure, C++, compiler intel/2017.02, Linux
Stop criteria(s);Best results from all runs
Submission date; 2024/04/08
ID;9
Author(s);Vilm Heinz, Petr Vilm, Zdenk Hanzlek
Reference;Heinz, V., Hanzlek, Z., & Vilim, P. (2025). Reinforcement Learning for Search Tree Size Minimization in Constraint Programming: New Results on Scheduling Benchmarks, Computers & Industrial Engineering 209, 111413. https://doi.org/10.1016/j.cie.2025.111413
Date; 2024/10/10
Hardware / software;Unknown
Stop criteria(s);900 seconds
Submission date; 2024/10/10
ID;10
Author(s); Coelho, Jose and Vanhoucke, Mario
Reference; Coelho, Jose and Vanhoucke, Mario. 2024. Working paper 'Comparing and extending satisfiability solution methods for the resource-constrained project scheduling problem'
Date; 2024/08/01
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; 2024/08/01
ID;11
Author(s);PSPLIB report
Reference;Check PSPLIB website: http://www.om-db.wi.tum.de/psplib
Date; 1999/01/01
Hardware / software;Not reported
Stop criteria;Results reported from several authors, UBs, LBs and optimal runs
Submission date;28/05/2024
ID;1
Author(s); Demeulemeester, E. and Herroelen, W.
Reference;Demeulemeester, E., & Herroelen, W. (1992). A Branch-and-Bound Procedure for the Multiple Resource-Constrained Project Scheduling Problem. Management Science, 38(12), 1803-1818. http://www.jstor.org/stable/2632711
Date; 1992/01/01
Hardware / software; i7, 16GB, 2GHz, C++, Visual Studio 2015 (x64), Windows 10
Stop criteria;1m and 1h runs
Submission date; 2016/01/01
ID;2
Author(s); Klein, R. and Scholl, A.
Reference;Klein, R., & Scholl, A. (1999). Computing lower bounds by destructive improvement: An application to resource-constrained project scheduling. European Journal of Operational Research, 112(2), 322-346. https://doi.org/10.1016/S0377-2217(97)00442-6
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., & Vanhoucke, M. (2007). A Decomposition-Based Genetic Algorithm for the Resource-Constrained Project-Scheduling Problem. Operations Research, 55(3), 457-469. https://doi.org/10.1287/opre.1060.0358
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: 1000 runs x 500k schedules
Submission date; 2017/5/21
ID;4
Author(s); Andrei Horbach
Reference;Horbach, A. (2010). A Boolean satisfiability approach to the resource-constrained project scheduling problem. Annals of Operations Research, 181(1), 89–107. https://doi.org/10.1007/s10479-010-0693-2
Date;05/02/2010
Hardware / software;Dell Precision with Intel Core2Duo T6400 2.2GHz with 1 GB of RAM running under Windows XP (data extracted from table 5 and 6 in the paper)
Stop criteria(s);Maximal time 20 hours
Submission date;2024
ID;5
Author(s);Schutt, A., Feydy, T., Stuckey, P.J., Wallace, M.G.
Reference;Schutt, A., Feydy, T., Stuckey, P. J., & Wallace, M. G. (2011). Explaining the cumulative propagator. Constraints, 16(3), 250-282. https://doi.org/10.1007/s10601-010-9103-2
Date; 2011/07/01
Hardware / software;X86-64 architecture running GNU/Linux and a Intel(R) Xeon(R) CPU E54052 processor with 2 GHz. Code in Mercury using the G12 Constraint Programming Platform
Stop criteria(s);10 min, results reported in the paper as new results at the time of publication
Submission date; 2019/10/28
ID;6
Author(s);Petr Vilim
Reference;Vilim, P. (2011). Timetable Edge Finding Filtering Algorithm for Discrete Cumulative Resources. International Conference on AI and OR Techniques in Constriant Programming for Combinatorial Optimization Problems, 16. https://doi.org/10.1007/978-3-642-21311-3_22
Date;2011
Hardware / software;Intel(R) Core(TM)2 Duo CPU T9400 on 2.53GHz
Stop criteria;time limit for each improvement step is 60 seconds
Submission date;2021
ID;7
Author(s); Coelho, J. and Vanhoucke, M.
Reference;Coelho, J., & Vanhoucke, M. (2018). An exact composite lower bound strategy for the resource-constrained project scheduling problem. Computers & Operations Research, 93, 135-150. https://doi.org/10.1016/j.cor.2018.01.017
Date; 2017/06/01
Hardware / software; STEVIN HPC-UGent infrastructure, C++, compiler intel/2017.02, Linux
Stop criteria(s);Best results from all runs, with maximal run time of 1h
Submission date; 2017/12/31
ID;8
Author(s);Vanhoucke, M. and Coelho, J.
Reference;Vanhoucke, M., & Coelho, J. (2024). A matheuristic for the resource-constrained project scheduling problem. European Journal of Operational Research, 319(3), 711725. https://doi.org/10.1016/j.ejor.2024.07.016
Date;01/12/2024
Hardware / software; STEVIN HPC-UGent infrastructure, C++, compiler intel/2017.02, Linux
Stop criteria(s);Best results from all runs
Submission date; 2024/04/08
ID;9
Author(s);Vilm Heinz, Petr Vilm, Zdenk Hanzlek
Reference;Heinz, V., Hanzlek, Z., & Vilim, P. (2025). Reinforcement Learning for Search Tree Size Minimization in Constraint Programming: New Results on Scheduling Benchmarks, Computers & Industrial Engineering 209, 111413. https://doi.org/10.1016/j.cie.2025.111413
Date; 2024/10/10
Hardware / software;Unknown
Stop criteria(s);900 seconds
Submission date; 2024/10/10
ID;10
Author(s); Coelho, Jose and Vanhoucke, Mario
Reference; Coelho, Jose and Vanhoucke, Mario. 2024. Working paper 'Comparing and extending satisfiability solution methods for the resource-constrained project scheduling problem'
Date; 2024/08/01
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; 2024/08/01
ID;11
Author(s);PSPLIB report
Reference;Check PSPLIB website: http://www.om-db.wi.tum.de/psplib
Date; 1999/01/01
Hardware / software;Not reported
Stop criteria;Results reported from several authors, UBs, LBs and optimal runs
Submission date;28/05/2024
Relevant Results
Best Known Solutions
Original Instances
File Header
Title;J90
Description;Dataset proposed in the paper Kolisch, R., & Sprecher, A. (1997). PSPLIB - A project scheduling problem library. European Journal of Operational Research, 96(1), 205-216. https://doi.org/10.1016/S0377-2217(96)00170-1
Number;480
Format;sm
Description;Dataset proposed in the paper Kolisch, R., & Sprecher, A. (1997). PSPLIB - A project scheduling problem library. European Journal of Operational Research, 96(1), 205-216. https://doi.org/10.1016/S0377-2217(96)00170-1
Number;480
Format;sm
Date