JSPLib

The jobshop scheduling problem benchmark library

The JSPLib is an informal group of instances (ft, la, abz, orb, swv, yn, ta, dmu to which we added tai, long and short) that have been used to investigate solution methods for the jobshop problem. On this page we keep track of the best known solutions (BKS) and classify the instances based on difficulty.

The data and source code can be found in the Github repository This document is visible as a README.md in the Github folder jobshop or as a webpage

Table of Contents

• Jobshop instances
  • Overview of the jobshop benchmark
  • Classification of the jobshop instances
  • Formats
  • Publications
• Jobshop and variants using the standard format
  • Jobshop
  • No buffer jobshop (blocking)
  • No wait jobshop
  • Cumulative jobshop
  • Jobshop with operators
• Jobshop variants that require extra data
  • Jobshop with arbitrary precedences
  • Jobshop with setup times
  • Flexible jobshop
• Jobshop benchmark - JSPLib
  • Similar work
  • Best known solutions
  • Publications
• Test instances for algorithms

Overview of the jobshop benchmark library

All instances in the benchmark follow the standard jobshop format. The DaColTeppan instances use a conservative extension of the existing jobshop format.

Jobshop instances (332)

• 3 instances ft from Fischer and Thompson 1963
• 40 instances la from Lawrence 1984
• 5 instances abz from Adams, Balas and Zawack 1988
• 10 instances orb from Applegate and Cook 1991
• 20 instances swv from Storer, Wu and Vaccari 1992
• 4 instances yn from Yamada and Nakano 1992
• 80 instances ta from Taillard 1993
• 80 instances dmu from Demirkol, Mehta and Uzsoy 1998
• 90 instances tai from Da Col and Teppan 2022

Reentrant jobshop instances (24)

• 12 instances long from Da Col and Teppan 2022
• 12 instances short from Da Col and Teppan 2022

Classification of the jobshop instances

We use the following engines as references for the benchmark

• IBM ILOG CP Optimizer : representative of the CP-scheduling family of engines
• Google CP-SAT : representative of the lazy clause generation family of engines
• OptalCP : representative of the lazy clause generation family of engines

We have dropped Cplex from the jobshop tests due to poor performance of linear solvers as reported by multiple authors in the literature and confirmed by ourselves.

Instances are divided into

• easy : solved to optimality (with proof) in 1 minute by at least 1 reference engine
• medium : solved to optimality (with proof) in 1 hour by at least 1 reference engine
• hard : solved to optimality (with proof) in > 1h by at least 1 reference engine
• closed : allegedly solved to optimality. Most of the time the optimal solution is known because 2 different methods independently found equal upper and lower bounds. The problem moves to hard only when the optimality proof can be reproduced by a reference engine.
• open : no proof of optimality

Currently the instances divide as follows

• ft : 3 easy
• la : 39 easy, 1 medium
• abz : 2 easy, 2 medium, 1 hard
• orb : 10 easy
• swv : 7 easy, 4 medium, 6 hard, 3 open
• yn : 4 hard
• ta : 40 easy, 21 medium, 7 hard, 12 open
• dmu : 17 easy, 13 medium, 5 hard, 45 open
• tai : 50 easy, 40 open
• long : 11 easy, 1 medium
• short : 5 easy, 6 medium, 1 open

Previous versions of these results had some closed instances which we proceed to solve with OptalCP running for longer times to confirm their status of solved

Formats

There are three main formats, the standard, the DaColTeppan and the taillard

Standard format

#n #m
((machine duration ){m}\n){n}

Image from Da Col & Teppan

For instance l01 on standard format is

10	5	
1	21	0	53	4	95	3	55	2	34
0	21	3	52	4	16	2	26	1	71
3	39	4	98	1	42	2	31	0	12
1	77	0	55	4	79	2	66	3	77
0	83	3	34	2	64	1	19	4	37
1	54	2	43	4	79	0	92	3	62
3	69	4	77	1	87	2	87	0	93
2	38	0	60	1	41	3	24	4	83
3	17	1	49	4	25	0	44	2	98
4	77	3	79	2	43	1	75	0	96

Da Col Teppan format

#n #m
((machine duration )+ -1 -1\n){n}

Image from Da Col & Teppan

In the DaColTeppan format

• there can be any number of tasks per job
• there can be various tasks in a job running on the same machine (reentrance)
• the jobs end in a -1 -1

The DaColTeppan format is actually a format for the reentrant jobshop problem which is a generalization of the jobshop, common in some industrial environments like semiconductors

For instance

10	5	
1	21	0	53	-1  -1
0	21	3	52	 4	16	2	26	1	71   4	95	3	55	 2	34 -1 -1
3	39	4	98	 1	42	2	31	0	12  79	 2	66	3	77  -1 -1
1	77	0	55	 4  -1 -1
0	83	-1 -1
1	54	2	43	4	79	0	92	3	62   3	34	 2	64	 1	19	4	37 -1 -1
3	69	4	77	1	87	2	87	0	93  41	 3	24	 4	83  -1 -1
2	38	0	60	1	-1 -1
3	17	1	49	4	25	0	44	2	98 -1 -1
4	77	3	79	2	43	1	75	0	96 -1 -1

To be totally conservative, the format should remove the last two -1 -1 and consider the end of line is the separator between jobs. It is not hard to do a parser that accepts both.

Taillard format

The taillard format first lists the machines, then the durations

#n #m
((machine ){m}\n){n}
((duration ){m}\n){n}

For instance l01 in taillard format is

10	5	
1	0	4	3	2
0	3	4	2	1
3	4	1	2	0
1	0	4	2	3
0	3	2	1	4
1	2	4	0	3
3	4	1	2	0
2	0	1	3	4
3	1	4	0	2
4	3	2	1	0
21	53	95	55	34
21	52	16	26	71
39	98	42	31	12
77	55	79	66	77
83	34	64	19	37
54	43	79	92	62
69	77	87	87	93
38	60	41	24	83
17	49	25	44	98
77	79	43	75	96

Publications (instances)

The instances come from the following publications

• H. Fisher, G.L. Thompson (1963), Probabilistic learning combinations of local job-shop scheduling rules, J.F. Muth, G.L. Thompson (eds.), Industrial Scheduling, Prentice Hall, Englewood Cliffs, New Jersey, 225-251.

• Lawrence, S. (1984). Resource constrained project scheduling: An experimental investigation of heuristic scheduling techniques (Supplement). Graduate School of Industrial Administration, Carnegie-Mellon University.

• Adams, J., Balas, E., & Zawack, D. (1988). The shifting bottleneck procedure for job shop scheduling. Management science, 34(3), 391-401.

• Applagate, D., & Cook, W. (1991). A computational study of the job-shop scheduling instance. ORSA J. Comput, 3, 49-51.

• Storer, R. H., Wu, S. D., & Vaccari, R. (1992). New search spaces for sequencing instances with application to job shop 38 (1992) 1495–1509 Manage. Sci, 38, 1495-1509.

• T. Yamada, R. Nakano (1992), A genetic algorithm applicable to large-scale job-shop instances, R. Manner, B. Manderick (eds.),Parallel instance solving from nature 2, North-Holland, Amsterdam, 281-290

• Taillard, E. (1993). Benchmarks for basic scheduling problems. european journal of operational research, 64(2), 278-285.

• Demirkol, E., Mehta, S., & Uzsoy, R. (1998). Benchmarks for shop scheduling problems. European Journal of Operational Research, 109(1), 137-141.

• Da Col, G., & Teppan, E. C. (2022). Industrial-size job shop scheduling with constraint programming. Operations Research Perspectives, 9, 100249.

Jobshop variants

Many variants of the jobshop problem can be solved with the same data or simple addition of parameters

Jobshop

The classical jobshop problem has 2 constraints

• intrajob precedences

\[\forall j \in \mathrm{jobs}, \forall r \in \mathrm{ranks} \quad \mathrm{start}_j^r + \mathrm{Duration}_j^r \leq \mathrm{start}_j^{r+1}\]

• no overlap per machine

\[\forall m \in \mathrm{machines}, \forall j_1,j_2 \in \mathrm{jobs} \quad \left( \mathrm{start}\_{j_1}^m + \mathrm{Duration}\_{j_1}^m \leq \mathrm{start}\_{j_2}^m \right) \vee \left( \mathrm{start}\_{j_2}^m + \mathrm{Duration}\_{j_2}^m \leq \mathrm{start}\_{j_1}^m \right )\]

For commodity the later constraint can be written

\[\forall m \in \mathrm{machines} \quad \mathrm{noOverlap} \ \lbrace \ [ \mathrm{start}_j^m \dots \ \mathrm{start}_j^m + \mathrm{Duration}_j^m ] \mid j \in \mathrm{jobs} \ \rbrace\]

No buffer jobshop (blocking jobshop)

In the classic jobshop there is implicitly a buffer area in front of each machine where tasks can wait to be processed. In the non-buffer jobshop, also called blocking jobshop this area doesn’t exist, as a result a job (j,r)processed on machine m blocks this machine until (j,r+1) starts being processed on the next machine.

From this problem we introduce a new variable $\mathrm{end}_j^m$

• the tasks are variable length with a minimum length of $\mathrm{Duration}_j^m$

\[\forall j \in \mathrm{jobs}, \forall r \in \mathrm{machines} \quad \mathrm{start}_j^m + \mathrm{Duration}_j^m \leq \mathrm{end}_j^m\]

• for each job, the task of rank $r+1$ starts as soon as the task of rank $r$ ends

\[\forall j \in \mathrm{jobs}, \forall r \in \mathrm{ranks} \quad \mathrm{end}_j^r = \mathrm{start}_j^{r+1}\]

• no overlap per machine

\[\forall m \in \mathrm{machines}, \forall j_1,j_2 \in \mathrm{jobs}\quad \left( \mathrm{end}\_{j_1}^m \leq \mathrm{start}\_{j_2}^m \right) \vee \left( \mathrm{end}\_{j_2}^m \leq \mathrm{start}\_{j_1}^m \right )\]

or

\[\forall m \in \mathrm{machines} \quad \mathrm{noOverlap} \ \lbrace \ [ \mathrm{start}_j^m \dots \ \mathrm{end}_j^m ] \mid j \in \mathrm{jobs} \ \rbrace\]

The extra variables $\mathrm{end}$ can be pre-processed out of the equations

No-wait jobshop

In the no-wait jobshop variant, once the processing of a job has started, it has to go through all machines without interruption.

The equations are reminiscent of the blocking jobshop but without the variable length activities

• for each job, the task of rank $r+1$ starts as soon as the task of rank $r$ ends

\[\forall j \in \mathrm{jobs}, \forall r \in \mathrm{ranks} \quad \mathrm{end}_j^r = \mathrm{start}_j^{r+1}\]

• no overlap per machine

\[\forall m \in \mathrm{machines}, \forall j_1,j_2 \in \mathrm{jobs}\quad \left( \mathrm{end}\_{j_1}^m \leq \mathrm{start}\_{j_2}^m \right) \vee \left( \mathrm{end}\_{j_2}^m \leq \mathrm{start}\_{j_1}^m \right )\]

or

\[\forall m \in \mathrm{machines} \quad \mathrm{noOverlap} \ \lbrace \ [ \mathrm{start}_j^m \dots \ \mathrm{end}_j^m ] \mid j \in \mathrm{jobs} \ \rbrace\]

Cumulative jobshop

In the cumulative jobshop, the capacity of the capacity of the machines is not unitary anymore. In other words there is a limit $C_m$ on the number of tasks that can be simultaneously processed by machine $m$

The constraints of the problem are

• intrajob precedences

\[\forall j \in \mathrm{jobs}, \forall r \in \mathrm{ranks} \quad \mathrm{start}_j^r + \mathrm{Duration}_j^r \leq \mathrm{start}_j^{r+1}\]

• capacity per machine

\[\forall m \in \mathrm{machines}, \forall t \in \mathrm{time} \quad \sum_j \left( \mathrm{start}^m_j \leq t \lt \mathrm{start}^m_j + \mathrm{Duration}^m_j \right) \leq C_m\]

It is advisable to avoid having an unlimited number of equations, in this case because of the explicit dependency on time, even if it just for notation. We therefore introduce the functional notation for cumulative constraints

\[\forall m \in \mathrm{machines}\quad \mathrm{cumul}_m(t) = \sum_j \mathrm{step}(\mathrm{start}_j^m) - \mathrm{step}(\mathrm{start}_j^m + \mathrm{Duration}_j^m)\]

Here $\mathrm{step}(t)$ is the function that has value 1 at time $t$ and 0 otherwise, as a result $\mathrm{cumul}$ is a function of time. Each configuration of $\mathrm{start}_j^m$ values defines a different cumulative function.

The constraints of the problem become

• intrajob precedences

\[\forall j \in \mathrm{jobs}, \forall r \in \mathrm{ranks} \quad \mathrm{start}_j^r + \mathrm{Duration}_j^r \leq \mathrm{start}_j^{r+1}\]

• capacity per machine

\[\forall m \in \mathrm{machines}\quad \sum_j \mathrm{step}(\mathrm{start}_j^m) - \mathrm{step}(\mathrm{start}_j^m + \mathrm{Duration}_j^m) \leq C_m\]

Jobshop with operators - workers

In the jobshop with operators, workers have to be assigned to the machines while the tasks are being performed.

• when the operator assignment can be interrupted (preemptive operators) the problem becomes a jobshop with maximum number of simultaneous jobs.
• when the operator assignment cannot be interrupted (non-preemptive operators) the operators need to be assigned to jobs individually and they cannot be assigned to simultaneous jobs

Jobshop with preemptive operators

The constraints of the problem become

• intrajob precedences

\[\forall j \in \mathrm{jobs}, \forall r \in \mathrm{ranks} \quad \mathrm{start}_j^r + \mathrm{Duration}_j^r \leq \mathrm{start}_j^{r+1}\]

• no overlap per machine

\[\forall m \in \mathrm{machines} \quad \mathrm{noOverlap} \ \lbrace \ [ \mathrm{start}_j^m \dots \ \mathrm{start}_j^m + \mathrm{Duration}_j^m ] \mid j \in \mathrm{jobs} \ \rbrace\]

• maximum number of simultaneous tasks

\[\sum_m \sum_j \mathrm{step}(\mathrm{start}_j^m) - \mathrm{step}(\mathrm{start}_j^m + \mathrm{Duration}_j^m) \leq \mathrm{Op}\]

Other jobshop variants

Because these jobshop variants require extra data, we cannot run them over the standard benchmark

Jobshop with arbitrary precedences

Instead of having precedences only within the tasks of a job, there is a more general precedence graph

Jobshop with sequence dependent setup times

There are setup times in the machines to switch from one job to another

Notice that this variant is only interesting if the setup times are sequence-dependent. Otherwise it is equivalent to increase each task by the length of the setup time and to solve an usual jobshop

Flexible jobshop

The tasks of a job can be processed by any machine in a predefined group of similar machines.

Please refer to the flexible-jobshop section of this benchmark for more information

Jobshop benchmark - JSPLib

The JSPLib is an informal group of instances (ft, la, abz, orb, swv, yn, ta, dmu to which we added tai, short and long) that have been used to investigate solution methods for the jobshop problem. On this page we keep track of the best known solutions (BKS) and classify the instances based on difficulty.

An instance is considered

• easy if it is solved to optimality by a reference engine in < 1 minute
• medium if it is solved to optimality by a reference engine in < 1h
• hard if it is solved to optimality by a reference engine in > 1h
• closed if the combination of upper and lower bounds found in the literature allows concluding the value of the optimal solution is known
• open otherwise

For each instance we indicate the publication or engine that reaches that bound (lower or upper). When reporting the results:

• we give priority to engines over publications because of reproductibility of the results
• we give priority to the fastest engine to attain the bound
• when an engine attains a bound previously reported in the literature, we attribute the bound to the engine and remove the correponding paper from the list of relevant references

Other databases keep instead the first publication or method to have achieved that bound for historical reference. This work instead is meant for engine and algorithm developers to have means of reproducing the claimed results for comparison.

Similar work

Our work was inspired by the outstanding work of Naderi, Ruiz and Roshanaei Mixed-Integer Programming versus Constraint Programming for shop scheduling problems : New Results and Outlook [NRR2022] which compares CPO, Cplex, Gurobi and OR-tools on a benchmark of 6623 instances over 17 benchmarks with a timeout of 1h. They have made all the raw results available

We borrowed references for existing best known bounds from

• http://mistic.heig-vd.ch/taillard/problemes.dir/ordonnancement.dir/ordonnancement.html
• https://github.com/thomasWeise/jsspInstancesAndResults
• http://jobshop.jjvh.nl/
• https://optimizizer.com/jobshop.php

The upper bounds available in optimizizer are verified before publication (which we don’t do directly - our verification is the fact that an engine achieves the same value). We encourage you to also visit his site.

We also think https://www.jobshoppuzzle.com/ is a very cool site with interactive visualizations of jobshop heuristics and solutions.

Best known solutions - JSPLib

If you visualize the markdown in Visual Studio Code you will have colors !

Fisher and Thompson (1963)

FT instances are also known as MT because the 1963 paper of Fisher and Thompson was published in the book “Industrial scheduling” by Muth and Thompson.

Instance	Size	Problem	LB	UB	Type	Solved by
ft06	6 x 6	jobshop	55	55	easy	CPO in < 1 min
ft10	10 x 10	jobshop	930	930	easy	CPO in < 1 min
ft20	20 x 5	jobshop	1165	1165	easy	CPO in < 1 min

Lawrence (1984)

Instance	Size	Problem	LB	UB	Type	Solved by
la01	10 x 5	jobshop	666	666	easy	CPO in < 1 min
la02	10 x 5	jobshop	655	655	easy	CPO in < 1 min
la03	10 x 5	jobshop	597	597	easy	CPO in < 1 min
la04	10 x 5	jobshop	590	590	easy	CPO in < 1 min
la05	10 x 5	jobshop	593	593	easy	CPO in < 1 min
la06	15 x 5	jobshop	926	926	easy	CPO in < 1 min
la07	15 x 5	jobshop	890	890	easy	CPO in < 1 min
la08	15 x 5	jobshop	863	863	easy	CPO in < 1 min
la09	15 x 5	jobshop	951	951	easy	CPO in < 1 min
la10	15 x 5	jobshop	958	958	easy	CPO in < 1 min
la11	20 x 5	jobshop	1222	1222	easy	CPO in < 1 min
la12	20 x 5	jobshop	1039	1039	easy	CPO in < 1 min
la13	20 x 5	jobshop	1150	1150	easy	CPO in < 1 min
la14	20 x 5	jobshop	1292	1292	easy	CPO in < 1 min
la15	20 x 5	jobshop	1207	1207	easy	CPO in < 1 min
la16	10 x 10	jobshop	945	945	easy	CPO in < 1 min
la17	10 x 10	jobshop	784	784	easy	CPO in < 1 min
la18	10 x 10	jobshop	848	848	easy	CPO in < 1 min
la19	10 x 10	jobshop	842	842	easy	CPO in < 1 min
la20	10 x 10	jobshop	902	902	easy	CPO in < 1 min
la21	15 x 10	jobshop	1046	1046	easy	OptalCP in < 1 min
la22	15 x 10	jobshop	927	927	easy	CPO in < 1 min
la23	15 x 10	jobshop	1032	1032	easy	CPO in < 1 min
la24	15 x 10	jobshop	935	935	easy	CPO in < 1 min
la25	15 x 10	jobshop	977	977	easy	CPO in < 1 min
la26	20 x 10	jobshop	1218	1218	easy	CPO in < 1 min
la27	20 x 10	jobshop	1235	1235	easy	OptalCP in < 1 min
la28	20 x 10	jobshop	1216	1216	easy	CPO in < 1 min
la29	20 x 10	jobshop	1152	1152	medium	OptalCP in 5 min
la30	20 x 10	jobshop	1355	1355	easy	CPO in < 1 min
la31	30 x 10	jobshop	1784	1784	easy	CPO in < 1 min
la32	30 x 10	jobshop	1850	1850	easy	CPO in < 1 min
la33	30 x 10	jobshop	1719	1719	easy	CPO in < 1 min
la34	30 x 10	jobshop	1721	1721	easy	CPO in < 1 min
la35	30 x 10	jobshop	1888	1888	easy	CPO in < 1 min
la36	15 x 15	jobshop	1268	1268	easy	CPO in < 1 min
la37	15 x 15	jobshop	1397	1397	easy	CPO in < 1 min
la38	15 x 15	jobshop	1196	1196	easy	OptalCP in < 1 min
la39	15 x 15	jobshop	1233	1233	easy	CPO in < 1 min
la40	15 x 15	jobshop	1222	1222	easy	OptalCP in < 1 min

Adams, Balas and Zawack (1988)

Instance	Size	Problem	LB	UB	Type	Solved by
abz5	10 x 10	jobshop	1234	1234	easy	CPO in < 1 min
abz6	10 x 10	jobshop	943	943	easy	CPO in < 1 min
abz7	20 x 15	jobshop	656	656	medium	OptalCP in < 1h
abz8	20 x 15	jobshop	667	667	hard	OptalCP in 10h
abz9	20 x 15	jobshop	678	678	medium	OptalCP in < 1h

Various places report that “Henning A (2002). Praktische Job-Shop Scheduling-Probleme. Ph.D. thesis, Friedrich-Schiller-Universität Jena, Jena, Germany” as having found a solution of 665 for abz8, but the original document says their solution is 667 and 665 is a “solution from the literature”. We believe it is just a typing mistake in the sources they used. In any case OptalCP proves a lower bound of 667.

Applegate and Cook (1991)

Instance	Size	Problem	LB	UB	Type	Solved by
orb01	10 x 10	jobshop	1059	1059	easy	CPO in < 1 min
orb02	10 x 10	jobshop	888	888	easy	CPO in < 1 min
orb03	10 x 10	jobshop	1005	1005	easy	CPO in < 1 min
orb04	10 x 10	jobshop	1005	1005	easy	CPO in < 1 min
orb05	10 x 10	jobshop	887	887	easy	CPO in < 1 min
orb06	10 x 10	jobshop	1010	1010	easy	CPO in < 1 min
orb07	10 x 10	jobshop	397	397	easy	CPO in < 1 min
orb08	10 x 10	jobshop	899	899	easy	CPO in < 1 min
orb09	10 x 10	jobshop	934	934	easy	CPO in < 1 min
orb10	10 x 10	jobshop	944	944	easy	CPO in < 1 min

Storer, Wu and Vaccari (1992)

Instance	Size	Problem	LB	UB	Type	Solved by
swv01	20 x 10	jobshop	1407	1407	easy	OptalCP in < 1 min
swv02	20 x 10	jobshop	1475	1475	easy	OptalCP in < 1 min
swv03	20 x 10	jobshop	1398	1398	medium	CPO in < 1h
swv04	20 x 10	jobshop	1464	1464	medium	OptalCP in < 1h
swv05	20 x 10	jobshop	1424	1424	medium	OptalCP in < 1h
swv06	20 x 15	jobshop	1667	1667	hard	OptalCP in 40h
swv07	20 x 15	jobshop	1541	1594	open	lb OptalCP / ub GR2014
swv08	20 x 15	jobshop	1694	1751	open	lb OptalCP / ub Mu2015
swv09	20 x 15	jobshop	1655	1655	hard	OptalCP in 15h
swv10	20 x 15	jobshop	1692	1743	open	lb OptalCP / ub SS2018
swv11	50 x 10	jobshop	2983	2983	medium	OptalCP in < 1h
swv12	50 x 10	jobshop	2972	2972	medium	OptalCP in < 1h
swv13	50 x 10	jobshop	3104	3104	medium	OptalCP in < 1h
swv14	50 x 10	jobshop	2968	2968	medium	CPO in < 1h
swv15	50 x 10	jobshop	2885	2885	hard	OptalCP in 9h
swv16	50 x 10	jobshop	2924	2924	easy	CPO in < 1 min
swv17	50 x 10	jobshop	2794	2794	easy	CPO in < 1 min
swv18	50 x 10	jobshop	2852	2852	easy	CPO in < 1 min
swv19	50 x 10	jobshop	2843	2843	easy	CPO in < 1 min
swv20	50 x 10	jobshop	2823	2823	easy	CPO in < 1 min

Yamada Nakano (1992)

Instance	Size	Problem	LB	UB	Type	Solved by
yn1	20 x 20	jobshop	884	884	hard	OptalCP in 6h
yn2	20 x 20	jobshop	904	904	hard	OptalCP in 40h
yn3	20 x 20	jobshop	892	892	hard	OptalCP in 40h
yn4	20 x 20	jobshop	967	967	hard	OptalCP in 16h

Taillard (1993)

Instance	Size	Problem	LB	UB	Type	Solved by
ta01js	15 x 15	jobshop	1231	1231	easy	CPO in < 1 min
ta02js	15 x 15	jobshop	1244	1244	easy	OptalCP in < 1 min
ta03js	15 x 15	jobshop	1218	1218	easy	OptalCP in < 1 min
ta04js	15 x 15	jobshop	1175	1175	easy	OptalCP in < 1 min
ta05js	15 x 15	jobshop	1224	1224	easy	OptalCP in < 1 min
ta06js	15 x 15	jobshop	1238	1238	easy	OptalCP in < 1 min
ta07js	15 x 15	jobshop	1227	1227	easy	OptalCP in < 1 min
ta08js	15 x 15	jobshop	1217	1217	easy	OptalCP in < 1 min
ta09js	15 x 15	jobshop	1274	1274	easy	OptalCP in < 1 min
ta10js	15 x 15	jobshop	1241	1241	easy	OptalCP in < 1 min
ta11js	20 x 15	jobshop	1357	1357	medium	OptalCP in < 1h
ta12js	20 x 15	jobshop	1367	1367	medium	OptalCP in < 1h
ta13js	20 x 15	jobshop	1342	1342	medium	OptalCP in < 1h
ta14js	20 x 15	jobshop	1345	1345	easy	CPO in < 1 min
ta15js	20 x 15	jobshop	1339	1339	medium	OptalCP in < 1h
ta16js	20 x 15	jobshop	1360	1360	medium	OptalCP in < 1h
ta17js	20 x 15	jobshop	1462	1462	easy	OptalCP in < 1 min
ta18js	20 x 15	jobshop	1396	1396	medium	OptalCP in < 1h
ta19js	20 x 15	jobshop	1332	1332	medium	OptalCP in < 1h
ta20js	20 x 15	jobshop	1348	1348	medium	OptalCP in < 1h
ta21js	20 x 20	jobshop	1642	1642	medium	OptalCP < 1h
ta22js	20 x 20	jobshop	1600	1600	hard	OptalCP in 2h
ta23js	20 x 20	jobshop	1557	1557	hard	OptalCP in 2h
ta24js	20 x 20	jobshop	1644	1644	medium	OptalCP in < 1h
ta25js	20 x 20	jobshop	1595	1595	medium	OptalCP in < 1h
ta26js	20 x 20	jobshop	1643	1643	medium	OptalCP in 7h
ta27js	20 x 20	jobshop	1680	1680	medium	OptalCP in < 1h
ta28js	20 x 20	jobshop	1603	1603	medium	OptalCP in < 1h
ta29js	20 x 20	jobshop	1625	1625	hard	OptalCP in 2h
ta30js	20 x 20	jobshop	1562	1584	open	lb OptalCP / ub NS2002
ta31js	30 x 15	jobshop	1764	1764	medium	CPO in < 1h
ta32js	30 x 15	jobshop	1774	1784	open	lb CPO2015 / ub PSV2010
ta33js	30 x 15	jobshop	1791	1791	hard	OptalCP in 10h
ta34js	30 x 15	jobshop	1828	1828	medium	OptalCP in < 1h
ta35js	30 x 15	jobshop	2007	2007	easy	OptalCP in < 1 min
ta36js	30 x 15	jobshop	1819	1819	medium	OptalCP in < 1h
ta37js	30 x 15	jobshop	1771	1771	hard	OptalCP in 2h
ta38js	30 x 15	jobshop	1673	1673	hard	OptalCP in 7h
ta39js	30 x 15	jobshop	1795	1795	easy	OptalCP in < 1 min
ta40js	30 x 15	jobshop	1658	1669	open	lb OptalCP / ub GR2014
ta41js	30 x 20	jobshop	1926	2005	open	lb OptalCP / ub CPO2015
ta42js	30 x 20	jobshop	1900	1937	open	lb OptalCP / ub GR2014
ta43js	30 x 20	jobshop	1809	1846	open	lb CPO2015 / ub PLC2015
ta44js	30 x 20	jobshop	1961	1979	open	lb OptalCP / ub CS2022
ta45js	30 x 20	jobshop	1997	1997	medium	OptalCP in < 1h
ta46js	30 x 20	jobshop	1976	2004	open	lb OptalCP / ub GR2014
ta47js	30 x 20	jobshop	1827	1889	open	lb OptalCP / ub PLC2015
ta48js	30 x 20	jobshop	1921	1937	open	lb OptalCP / ub SS2018
ta49js	30 x 20	jobshop	1938	1960	open	lb OptalCP / ub LHW2024
ta50js	30 x 20	jobshop	1848	1923	open	lb OptalCP / ub PLC2015
ta51js	50 x 15	jobshop	2760	2760	easy	CPO in < 1 min
ta52js	50 x 15	jobshop	2756	2756	easy	OptalCP in < 1 min
ta53js	50 x 15	jobshop	2717	2717	easy	OptalCP in < 1 min
ta54js	50 x 15	jobshop	2839	2839	easy	CPO in < 1 min
ta55js	50 x 15	jobshop	2679	2679	easy	OptalCP in < 1 min
ta56js	50 x 15	jobshop	2781	2781	easy	OptalCP in < 1 min
ta57js	50 x 15	jobshop	2943	2943	easy	CPO in < 1 min
ta58js	50 x 15	jobshop	2885	2885	easy	CPO in < 1 min
ta59js	50 x 15	jobshop	2655	2655	easy	OptalCP in < 1 min
ta60js	50 x 15	jobshop	2723	2723	easy	OptalCP in < 1 min
ta61js	50 x 20	jobshop	2868	2868	easy	OptalCP in < 1 min
ta62js	50 x 20	jobshop	2869	2869	medium	OptalCP in < 1h
ta63js	50 x 20	jobshop	2755	2755	easy	OptalCP in < 1 min
ta64js	50 x 20	jobshop	2702	2702	easy	OptalCP in < 1 min
ta65js	50 x 20	jobshop	2725	2725	easy	OptalCP in < 1 min
ta66js	50 x 20	jobshop	2845	2845	easy	OptalCP in < 1 min
ta67js	50 x 20	jobshop	2825	2825	hard	OptalCP in 4h
ta68js	50 x 20	jobshop	2784	2784	easy	OptalCP in < 1 min
ta69js	50 x 20	jobshop	3071	3071	easy	OptalCP in < 1 min
ta70js	50 x 20	jobshop	2995	2995	medium	CPO in < 1h
ta71js	100 x 20	jobshop	5464	5464	easy	OptalCP in < 1 min
ta72js	100 x 20	jobshop	5181	5181	easy	OptalCP in < 1 min
ta73js	100 x 20	jobshop	5568	5568	easy	OptalCP in < 1 min
ta74js	100 x 20	jobshop	5339	5339	easy	OptalCP in < 1 min
ta75js	100 x 20	jobshop	5392	5392	medium	CPO in < 1h
ta76js	100 x 20	jobshop	5342	5342	easy	OptalCP in < 1 min
ta77js	100 x 20	jobshop	5436	5436	easy	OptalCP in < 1 min
ta78js	100 x 20	jobshop	5394	5394	easy	OptalCP in < 1 min
ta79js	100 x 20	jobshop	5358	5358	easy	OptalCP in < 1 min
ta80js	100 x 20	jobshop	5183	5183	easy	OptalCP in < 1 min

Demikol, Mehta and Uzsoy (1998)

Instance	Size	Problem	LB	UB	Type	Solved by
dmu01	20 x 15	jobshop	2563	2563	medium	OptalCP in < 1h
dmu02	20 x 15	jobshop	2706	2706	medium	OptalCP in < 1h
dmu03	20 x 15	jobshop	2731	2731	medium	CPO in < 1h
dmu04	20 x 15	jobshop	2669	2669	medium	OptalCP in < 1h
dmu05	20 x 15	jobshop	2749	2749	medium	OptalCP in < 1h
dmu06	20 x 20	jobshop	3244	3244	hard	OptalCP in 2h
dmu07	20 x 20	jobshop	3046	3046	hard	OptalCP in 3h
dmu08	20 x 20	jobshop	3188	3188	medium	OptalCP in < 1h
dmu09	20 x 20	jobshop	3092	3092	medium	OptalCP in < 1h
dmu10	20 x 20	jobshop	2984	2984	medium	OptalCP in < 1h
dmu11	30 x 15	jobshop	3402	3430	open	lb OptalCP / ub PLC2015
dmu12	30 x 15	jobshop	3481	3492	open	lb OptalCP / ub SS2018
dmu13	30 x 15	jobshop	3681	3681	hard	OptalCP in 3h
dmu14	30 x 15	jobshop	3394	3394	easy	OptalCP in < 1 min
dmu15	30 x 15	jobshop	3343	3343	easy	OptalCP in < 1 min
dmu16	30 x 20	jobshop	3734	3750	open	lb CPO2015 / ub LHW2024
dmu17	30 x 20	jobshop	3733	3812	open	lb OptalCP / ub LHW2024
dmu18	30 x 20	jobshop	3844	3844	hard	OptalCP in 10h
dmu19	30 x 20	jobshop	3707	3764	open	lb OptalCP / ub CS2022
dmu20	30 x 20	jobshop	3632	3699	open	lb OptalCP / ub LHW2024
dmu21	40 x 15	jobshop	4380	4380	easy	OptalCP in < 1 min
dmu22	40 x 15	jobshop	4725	4725	easy	CPO in < 1 min
dmu23	40 x 15	jobshop	4668	4668	easy	CPO in < 1 min
dmu24	40 x 15	jobshop	4648	4648	easy	CPO in < 1 min
dmu25	40 x 15	jobshop	4164	4164	easy	CPO in < 1 min
dmu26	40 x 20	jobshop	4647	4647	medium	OptalCP < 1h
dmu27	40 x 20	jobshop	4848	4848	medium	OptalCP in < 1h
dmu28	40 x 20	jobshop	4692	4692	easy	OptalCP in < 1 min
dmu29	40 x 20	jobshop	4691	4691	easy	OptalCP in < 1 min
dmu30	40 x 20	jobshop	4732	4732	medium	OptalCP < 1h
dmu31	50 x 15	jobshop	5640	5640	easy	CPO in < 1 min
dmu32	50 x 15	jobshop	5927	5927	easy	CPO in < 1 min
dmu33	50 x 15	jobshop	5728	5728	easy	CPO in < 1 min
dmu34	50 x 15	jobshop	5385	5385	easy	CPO in < 1 min
dmu35	50 x 15	jobshop	5635	5635	easy	CPO in < 1 min
dmu36	50 x 20	jobshop	5621	5621	easy	OptalCP in < 1 min
dmu37	50 x 20	jobshop	5851	5851	medium	CPO in < 1h
dmu38	50 x 20	jobshop	5713	5713	medium	OptalCP in < 1h
dmu39	50 x 20	jobshop	5747	5747	easy	OptalCP in < 1 min
dmu40	50 x 20	jobshop	5577	5577	easy	OptalCP in < 1 min
dmu41	20 x 15	jobshop	3176	3248	open	lb OptalCP / ub PLC2015
dmu42	20 x 15	jobshop	3339	3390	open	lb OptalCP / ub SS2018
dmu43	20 x 15	jobshop	3441	3441	hard	OptalCP in 8h
dmu44	20 x 15	jobshop	3414	3475	open	lb OptalCP / ub SS2018
dmu45	20 x 15	jobshop	3217	3266	open	lb OptalCP / ub CS2022
dmu46	20 x 20	jobshop	3780	4035	open	lb OptalCP / ub GR2014
dmu47	20 x 20	jobshop	3714	3939	open	lb OptalCP / ub GR2014
dmu48	20 x 20	jobshop	3628	3763	open	lb OptalCP / ub SS2018
dmu49	20 x 20	jobshop	3543	3706	open	lb OptalCP / ub LHW2024
dmu50	20 x 20	jobshop	3618	3729	open	lb OptalCP / ub PLC2015
dmu51	30 x 15	jobshop	4070	4156	open	lb OptalCP / ub SS2018
dmu52	30 x 15	jobshop	4203	4297	open	lb OptalCP / ub LHW2024
dmu53	30 x 15	jobshop	4248	4378	open	lb OptalCP / ub CS2022
dmu54	30 x 15	jobshop	4277	4361	open	lb OptalCP / ub CS2022
dmu55	30 x 15	jobshop	4191	4258	open	lb OptalCP / ub LHW2024
dmu56	30 x 20	jobshop	4755	4939	open	lb OptalCP / ub XLGG2022
dmu57	30 x 20	jobshop	4462	4647	open	lb OptalCP / ub XLGG2022
dmu58	30 x 20	jobshop	4484	4701	open	lb OptalCP / ub CS2022
dmu59	30 x 20	jobshop	4366	4607	open	lb OptalCP / ub LHW2024
dmu60	30 x 20	jobshop	4468	4721	open	lb OptalCP / ub CS2022
dmu61	40 x 15	jobshop	5038	5169	open	lb OptalCP / ub LHW2024
dmu62	40 x 15	jobshop	5176	5247	open	lb OptalCP / ub LHW2024
dmu63	40 x 15	jobshop	5245	5312	open	lb OptalCP / ub LHW2024
dmu64	40 x 15	jobshop	5155	5226	open	lb OptalCP / ub CS2022
dmu65	40 x 15	jobshop	5122	5173	open	lb OptalCP / ub LHW2024
dmu66	40 x 20	jobshop	5526	5701	open	lb OptalCP / ub CS2022
dmu67	40 x 20	jobshop	5661	5779	open	lb OptalCP / ub SS2018
dmu68	40 x 20	jobshop	5513	5763	open	lb OptalCP / ub CS2022
dmu69	40 x 20	jobshop	5511	5688	open	lb OptalCP / ub CS2022
dmu70	40 x 20	jobshop	5633	5868	open	lb OptalCP / ub CS2022
dmu71	50 x 15	jobshop	6129	6207	open	lb OptalCP / ub CS2022
dmu72	50 x 15	jobshop	6434	6463	open	lb CdGKGC2025 / ub SS2018
dmu73	50 x 15	jobshop	6107	6136	open	lb OptalCP / ub CS2022
dmu74	50 x 15	jobshop	6168	6196	open	lb OptalCP / ub SS2018
dmu75	50 x 15	jobshop	6123	6189	open	lb OptalCP / ub SS2018
dmu76	50 x 20	jobshop	6479	6718	open	lb OptalCP / ub CS2022
dmu77	50 x 20	jobshop	6520	6747	open	lb OptalCP / ub CS2022
dmu78	50 x 20	jobshop	6643	6755	open	lb OptalCP / ub CS2022
dmu79	50 x 20	jobshop	6720	6910	open	lb OptalCP / ub CS2022
dmu80	50 x 20	jobshop	6460	6634	open	lb OptalCP / ub CS2022

Da Col and Teppan (2022)

Instance	Size	Problem	LB	UB	Type	Solved by
tai_j10_m10_1	10 x 10	jobshop	8219	8219	easy	OptalCP in < 1 min
tai_j10_m10_2	10 x 10	jobshop	7416	7416	easy	OptalCP in < 1 min
tai_j10_m10_3	10 x 10	jobshop	8094	8094	easy	OptalCP in < 1 min
tai_j10_m10_4	10 x 10	jobshop	8657	8657	easy	OptalCP in < 1 min
tai_j10_m10_5	10 x 10	jobshop	7936	7936	easy	OptalCP in < 1 min
tai_j10_m10_6	10 x 10	jobshop	8509	8509	easy	OptalCP in < 1 min
tai_j10_m10_7	10 x 10	jobshop	8299	8299	easy	OptalCP in < 1 min
tai_j10_m10_8	10 x 10	jobshop	7788	7788	easy	OptalCP in < 1 min
tai_j10_m10_9	10 x 10	jobshop	8300	8300	easy	OptalCP in < 1 min
tai_j10_m10_10	10 x 10	jobshop	8481	8481	easy	OptalCP in < 1 min
tai_j10_m100_1	10 x 100	jobshop	56609	56609	easy	OptalCP in < 1 min
tai_j10_m100_2	10 x 100	jobshop	52330	52330	easy	OptalCP in < 1 min
tai_j10_m100_3	10 x 100	jobshop	56412	56412	easy	OptalCP in < 1 min
tai_j10_m100_4	10 x 100	jobshop	54889	54889	easy	OptalCP in < 1 min
tai_j10_m100_5	10 x 100	jobshop	54603	54603	easy	OptalCP in < 1 min
tai_j10_m100_6	10 x 100	jobshop	53723	53723	easy	OptalCP in < 1 min
tai_j10_m100_7	10 x 100	jobshop	55456	55456	easy	OptalCP in < 1 min
tai_j10_m100_8	10 x 100	jobshop	56466	56466	easy	OptalCP in < 1 min
tai_j10_m100_9	10 x 100	jobshop	55096	55096	easy	OptalCP in < 1 min
tai_j10_m100_10	10 x 100	jobshop	56661	56661	easy	OptalCP in < 1 min
tai_j10_m1000_1	10 x 1000	jobshop	515370	515370	easy	OptalCP in < 1 min
tai_j10_m1000_2	10 x 1000	jobshop	513525	513525	easy	OptalCP in < 1 min
tai_j10_m1000_3	10 x 1000	jobshop	508161	508161	easy	OptalCP in < 1 min
tai_j10_m1000_4	10 x 1000	jobshop	513814	513814	easy	OptalCP in < 1 min
tai_j10_m1000_5	10 x 1000	jobshop	517020	517020	easy	OptalCP in < 1 min
tai_j10_m1000_6	10 x 1000	jobshop	517777	517777	easy	OptalCP in < 1 min
tai_j10_m1000_7	10 x 1000	jobshop	514921	514921	easy	OptalCP in < 1 min
tai_j10_m1000_8	10 x 1000	jobshop	522277	522277	easy	OptalCP in < 1 min
tai_j10_m1000_9	10 x 1000	jobshop	511213	511213	easy	OptalCP in < 1 min
tai_j10_m1000_10	10 x 1000	jobshop	509855	509855	easy	OptalCP in < 1 min
tai_j100_m10_1	100 x 10	jobshop	54951	54951	easy	OptalCP in < 1 min
tai_j100_m10_2	100 x 10	jobshop	57160	57160	easy	OptalCP in < 1 min
tai_j100_m10_3	100 x 10	jobshop	54166	54166	easy	OptalCP in < 1 min
tai_j100_m10_4	100 x 10	jobshop	54371	54371	easy	OptalCP in < 1 min
tai_j100_m10_5	100 x 10	jobshop	56142	56142	easy	OptalCP in < 1 min
tai_j100_m10_6	100 x 10	jobshop	52447	52447	easy	OptalCP in < 1 min
tai_j100_m10_7	100 x 10	jobshop	54051	54051	easy	OptalCP in < 1 min
tai_j100_m10_8	100 x 10	jobshop	55624	55624	easy	OptalCP in < 1 min
tai_j100_m10_9	100 x 10	jobshop	54210	54210	easy	OptalCP in < 1 min
tai_j100_m10_10	100 x 10	jobshop	55464	55464	easy	OptalCP in < 1 min
tai_j100_m100_1	100 x 100	jobshop	62843	77127	open	lb OptalCP / ub OptalCP
tai_j100_m100_2	100 x 100	jobshop	62814	77322	open	lb OptalCP / ub OptalCP
tai_j100_m100_3	100 x 100	jobshop	61533	76910	open	lb OptalCP / ub OptalCP
tai_j100_m100_4	100 x 100	jobshop	64742	78604	open	lb OptalCP / ub OptalCP
tai_j100_m100_5	100 x 100	jobshop	61766	78023	open	lb OptalCP / ub OptalCP
tai_j100_m100_6	100 x 100	jobshop	61360	77895	open	lb OptalCP / ub OptalCP
tai_j100_m100_7	100 x 100	jobshop	64040	77670	open	lb OptalCP / ub OptalCP
tai_j100_m100_8	100 x 100	jobshop	63224	78031	open	lb OptalCP / ub OptalCP
tai_j100_m100_9	100 x 100	jobshop	62631	79419	open	lb OptalCP / ub OptalCP
tai_j100_m100_10	100 x 100	jobshop	64866	77837	open	lb OptalCP / ub OptalCP
tai_j100_m1000_1	100 x 1000	jobshop	522298	544732	open	lb OptalCP / ub OptalCP
tai_j100_m1000_2	100 x 1000	jobshop	530375	546598	open	lb OptalCP / ub OptalCP
tai_j100_m1000_3	100 x 1000	jobshop	530560	549372	open	lb OptalCP / ub OptalCP
tai_j100_m1000_4	100 x 1000	jobshop	527101	545138	open	lb OptalCP / ub OptalCP
tai_j100_m1000_5	100 x 1000	jobshop	517728	545535	open	lb OptalCP / ub OptalCP
tai_j100_m1000_6	100 x 1000	jobshop	522907	545730	open	lb OptalCP / ub OptalCP
tai_j100_m1000_7	100 x 1000	jobshop	522537	546899	open	lb OptalCP / ub OptalCP
tai_j100_m1000_8	100 x 1000	jobshop	526428	549337	open	lb OptalCP / ub OptalCP
tai_j100_m1000_9	100 x 1000	jobshop	528097	550693	open	lb OptalCP / ub OptalCP
tai_j100_m1000_10	100 x 1000	jobshop	521766	543797	open	lb OptalCP / ub OptalCP
tai_j1000_m10_1	1000 x 10	jobshop	515334	515334	easy	OptalCP in < 1 min
tai_j1000_m10_2	1000 x 10	jobshop	509226	509226	easy	OptalCP in < 1 min
tai_j1000_m10_3	1000 x 10	jobshop	517493	517493	easy	OptalCP in < 1 min
tai_j1000_m10_4	1000 x 10	jobshop	519369	519369	easy	OptalCP in < 1 min
tai_j1000_m10_5	1000 x 10	jobshop	513881	513881	easy	OptalCP in < 1 min
tai_j1000_m10_6	1000 x 10	jobshop	511932	511932	easy	OptalCP in < 1 min
tai_j1000_m10_7	1000 x 10	jobshop	523900	523900	easy	OptalCP in < 1 min
tai_j1000_m10_8	1000 x 10	jobshop	513101	513101	easy	OptalCP in < 1 min
tai_j1000_m10_9	1000 x 10	jobshop	508701	508701	easy	OptalCP in < 1 min
tai_j1000_m10_10	1000 x 10	jobshop	521360	521360	easy	OptalCP in < 1 min
tai_j1000_m100_1	1000 x 100	jobshop	525343	539120	open	lb OptalCP / ub OptalCP
tai_j1000_m100_2	1000 x 100	jobshop	528088	540895	open	lb OptalCP / ub OptalCP
tai_j1000_m100_3	1000 x 100	jobshop	522793	534794	open	lb OptalCP / ub OptalCP
tai_j1000_m100_4	1000 x 100	jobshop	524271	536317	open	lb OptalCP / ub OptalCP
tai_j1000_m100_5	1000 x 100	jobshop	531216	532016	open	lb OptalCP / ub OptalCP
tai_j1000_m100_6	1000 x 100	jobshop	518763	535189	open	lb OptalCP / ub OptalCP
tai_j1000_m100_7	1000 x 100	jobshop	527093	535894	open	lb OptalCP / ub OptalCP
tai_j1000_m100_8	1000 x 100	jobshop	519524	533985	open	lb OptalCP / ub OptalCP
tai_j1000_m100_9	1000 x 100	jobshop	520889	539511	open	lb OptalCP / ub OptalCP
tai_j1000_m100_10	1000 x 100	jobshop	529112	540884	open	lb OptalCP / ub OptalCP
tai_j1000_m1000_1	1000 x 1000	jobshop	549392	877062	open	lb OptalCP / ub Hexaly2024
tai_j1000_m1000_2	1000 x 1000	jobshop	549043	877115	open	lb OptalCP / ub Hexaly2024
tai_j1000_m1000_3	1000 x 1000	jobshop	552580	878805	open	lb OptalCP / ub Hexaly2024
tai_j1000_m1000_4	1000 x 1000	jobshop	547670	876363	open	lb OptalCP / ub Hexaly2024
tai_j1000_m1000_5	1000 x 1000	jobshop	545193	877562	open	lb OptalCP / ub Hexaly2024
tai_j1000_m1000_6	1000 x 1000	jobshop	547286	876067	open	lb OptalCP / ub Hexaly2024
tai_j1000_m1000_7	1000 x 1000	jobshop	545877	875891	open	lb OptalCP / ub Hexaly2024
tai_j1000_m1000_8	1000 x 1000	jobshop	549220	876456	open	lb OptalCP / ub Hexaly2024
tai_j1000_m1000_9	1000 x 1000	jobshop	543559	875914	open	lb OptalCP / ub Hexaly2024
tai_j1000_m1000_10	1000 x 1000	jobshop	541530	874820	open	lb OptalCP / ub Hexaly2024

DaCol and Teppan - reentrant jobshop (2022)

Instance	Size	Problem	LB	UB	Type	Solved by
long-100-10000-1	103 x 100	reentrant jobshop	600000	600000	easy	OptalCP in < 1 min
long-100-10000-2	103 x 100	reentrant jobshop	600000	600000	easy	OptalCP in < 1 min
long-100-10000-3	103 x 100	reentrant jobshop	600000	600000	easy	OptalCP in < 1 min
long-1000-10000-1	1002 x 1000	reentrant jobshop	600000	600000	easy	OptalCP in < 1 min
long-1000-10000-2	1002 x 1000	reentrant jobshop	600000	600000	easy	OptalCP in < 1 min
long-1000-10000-3	1002 x 1000	reentrant jobshop	600000	600000	easy	OptalCP in < 1 min
long-100-100000-1	109 x 100	reentrant jobshop	600000	600000	easy	OptalCP in < 1 min
long-100-100000-2	114 x 100	reentrant jobshop	600000	600000	medium	OptalCP in < 1h
long-100-100000-3	109 x 100	reentrant jobshop	600000	600000	easy	OptalCP in < 1 min
long-1000-100000-1	1002 x 1000	reentrant jobshop	600000	600000	easy	OptalCP in < 1 min
long-1000-100000-2	1002 x 1000	reentrant jobshop	600000	600000	easy	OptalCP in < 1 min
long-1000-100000-3	1003 x 1000	reentrant jobshop	600000	600000	easy	OptalCP in < 1 min
short-100-10000-1	2162 x 100	reentrant jobshop	600000	600000	easy	OptalCP in < 1 min
short-100-10000-2	2192 x 100	reentrant jobshop	600000	600000	easy	OptalCP in < 1 min
short-100-10000-3	2169 x 100	reentrant jobshop	600000	600000	easy	OptalCP in < 1 min
short-1000-10000-1	2882 x 1000	reentrant jobshop	600000	600000	easy	OptalCP in < 1 min
short-1000-10000-2	2863 x 1000	reentrant jobshop	600000	600000	easy	OptalCP in < 1 min
short-1000-10000-3	2897 x 1000	reentrant jobshop	600000	600000	medium	OptalCP in < 1h
short-100-100000-1	20685 x 100	reentrant jobshop	600000	600000	medium	OptalCP in < 1h
short-100-100000-2	20870 x 100	reentrant jobshop	600000	600000	medium	OptalCP in < 1h
short-100-100000-3	20767 x 100	reentrant jobshop	600000	600000	medium	OptalCP in < 1h
short-1000-100000-1	21280 x 1000	reentrant jobshop	600000	600038	open	lb OptalCP / ub OptalCP
short-1000-100000-2	21349 x 1000	reentrant jobshop	600000	600000	medium	OptalCP in < 1h
short-1000-100000-3	21338 x 1000	reentrant jobshop	600000	600000	medium	OptalCP in < 1h

DaCol and Tepan report instance short-1000-100000-1 was solved to optimality by CP Optimizer in 6h which we haven’t been able to reproduce (with CPO any other solver). We are still investigating

Publications (best known solutions)

The upper and lower bounds come from

• NS2002 (1 bound - ta30js) : Nowicki, E., & Smutnicki, C. (2002). Some new tools to solve the job shop problem. Raport serii: Preprinty, 60.

• PSV2010 (1 bound - ta32js) : Pardalos, P. M., Shylo, O. V., & Vazacopoulos, A. (2010). Solving job shop scheduling problems utilizing the properties of backbone and “big valley”. Computational Optimization and Applications, 47, 61-76.

• GR2014 (6 bounds in dmu, tajs and swv) : Gonçalves, J. F., & Resende, M. G. (2014). An extended Akers graphical method with a biased random‐key genetic algorithm for job‐shop scheduling. International Transactions in Operational Research, 21(2), 215-246.

• CPO2015 (4 bounds in dmu and tajs):

  • Vilím, P., Laborie, P., & Shaw, P. (2015). Failure-directed search for constraint-based scheduling. In Integration of AI and OR Techniques in Constraint Programming: 12th International Conference, CPAIOR 2015, Barcelona, Spain, May 18-22, 2015, Proceedings 12 (pp. 437-453). Springer International Publishing.

  • Vilım, P., Laborie, P., & Shaw, P. Failure-directed Search for Constraint-based Scheduling Detailed Experimental Results.

• Mu2015 (1 bound - swv08) : Personal communication to optimizizer, probably based on Murovec, B. (2015). Job-shop local-search move evaluation without direct consideration of the criterion’s value. European Journal of Operational Research, 241(2), 320-329.

• PLC2015 (6 bounds in dmu and tajs) : Peng, B., Lü, Z., & Cheng, T. C. E. (2015). A tabu search/path relinking algorithm to solve the job shop scheduling problem. Computers & Operations Research, 53, 154-164.

• SS2018 (11 bounds in dmu and swv) : Shylo, O. V., & Shams, H. (2018). Boosting binary optimization via binary classification: A case study of job shop scheduling

• CS2022 (19 bounds in dmu and tajs) : Constantino, O. H., & Segura, C. (2022). A parallel memetic algorithm with explicit management of diversity for the job shop scheduling problem. Applied Intelligence, 52(1), 141-153.

• XLGG2022 (2 bounds in dmu) : Xie, J., Li, X., Gao, L., & Gui, L. (2022). A hybrid algorithm with a new neighborhood structure for job shop scheduling problems. Computers & Industrial Engineering, 169, 108205.

• Hexaly2024 (10 bounds - tai) : Lea Blaise (2014) https://www.hexaly.com/benchmarks/hexaly-vs-cp-optimizer-vs-CP-SAT-on-the-job-shop-scheduling-problem-jssp

• LHW2024 (12 bounds - dmu, tajs) : Mingjie Li, Jin-Kao Hao & Qinghua Wu (2025). Combining Hash-based Tabu Search and Frequent Pattern Mining for Job-Shop Scheduling. IISE Transactions, 1–16.

• CdGKGC2025 (1 bound dmu72) : Marc-Emmanuel Coupvent des Graviers, Lotfi Kobrosly, Christophe Guettier, and Tristan Cazenave (2025). Updating Lower and Upper Bounds for the Job-Shop Scheduling Problem Test Instances CoRR abs/2504.16106

All other bounds were found by OptalCP

Test instances

Reference tests

We provide these tests as a reference, you should get something similar on your hardware (multi-core engines are inherently non-deterministic hence each run returns slightly different results) or find an explanation of why the engines don’t behave as expected. We strongly encourage you to run all engines you want to compare against on your own hardware.

LA instances

On an Windows PC with an i7 4-core 3.3GHz 32GB ram in 600 seconds

• OptalCP Academic Version 2025.6.1 with 2 FDS, 1 FDSLB, 1 LNS (3 provers, 1 searcher)
• CP-SAT V9.14.6206 with default configuration (its log reports running 8 workers)

Instance	OptalCP	CP-SAT
la01	666 in 0s	666 in 0s
la02	655 in 0s	655 in 0s
la03	597 in 0s	597 in 0s
la04	590 in 0s	590 in 0s
la05	593 in 0s	593 in 0s
la06	926 in 0s	926 in 0s
la07	890 in 0s	890 in 0s
la08	863 in 0s	863 in 0s
la09	951 in 0s	951 in 0s
la10	958 in 0s	958 in 0s
la11	1222 in 0s	1222 in 0s
la12	1039 in 0s	1039 in 0s
la13	1150 in 0s	1150 in 0s
la14	1292 in 0s	1292 in 0s
la15	1207 in 0s	1207 in 0s
la16	945 in 0s	945 in 0s
la17	784 in 0s	784 in 0s
la18	848 in 0s	848 in 0s
la19	842 in 0s	842 in 1s
la20	902 in 0s	902 in 0s
la21	1046 in 2s	1046 in 49s
la22	927 in 0s	927 in 3s
la23	1032 in 0s	1032 in 0s
la24	935 in 1s	935 in 12s
la25	977 in 1s	977 in 11s
la26	1218 in 0s	1218 in 2s
la27	1235 in 9s	1235 in 9s
la28	1216 in 0s	1216 in 3s
la29	1152 in 217s	1130 .. 1162 in 600s
la30	1355 in 0s	1355 in 1s
la31	1784 in 0s	1784 in 1s
la32	1850 in 0s	1850 in 0s
la33	1719 in 0s	1719 in 1s
la34	1721 in 0s	1721 in 1s
la35	1888 in 0s	1888 in 0s
la36	1268 in 0s	1268 in 6s
la37	1397 in 0s	1397 in 1s
la38	1196 in 9s	1196 in 148s
la39	1233 in 0s	1233 in 2s
la40	1222 in 2s	1222 in 23s

TA instances

On an Windows PC with an i7 4-core 3.3GHz 32GB ram in 600 seconds

• OptalCP Academic Version 2025.6.1 with 2 FDS, 1 FDSLB, 1 LNS (3 provers, 1 searcher)
• CP-SAT V9.14.6206 with default configuration (its log reports running 8 workers)

Instance	OptalCP	CP-SAT
ta01js	1231 in 0s	1231 in 6s
ta02js	1244 in 2s	1244 in 44s
ta03js	1218 in 2s	1218 in 19s
ta04js	1175 in 2s	1175 in 53s
ta05js	1224 in 12s	1224 in 352s
ta06js	1238 in 163s	1203 .. 1238 in 600s
ta07js	1227 in 14s	1227 in 200s
ta08js	1217 in 8s	1217 in 130s
ta09js	1274 in 7s	1274 in 84s
ta10js	1241 in 2s	1241 in 20s
ta11js	1326 .. 1365 in 600s	1310 .. 1373 in 600s
ta12js	1367 in 231s	1352 .. 1387 in 600s
ta13js	1325 .. 1342 in 600s	1279 .. 1348 in 600s
ta14js	1345 in 0s	1345 in 9s
ta15js	1331 .. 1339 in 600s	1304 .. 1351 in 600s
ta16js	1343 .. 1363 in 600s	1300 .. 1370 in 600s
ta17js	1462 in 3s	1462 in 88s
ta18js	1389 .. 1398 in 600s	1361 .. 1414 in 600s
ta19js	1327 .. 1343 in 600s	1299 .. 1368 in 600s
ta20js	1338 .. 1351 in 600s	1316 .. 1363 in 600s
ta21js	1625 .. 1653 in 600s	1583 .. 1655 in 600s
ta22js	1544 .. 1616 in 600s	1533 .. 1613 in 600s
ta23js	1513 .. 1564 in 600s	1496 .. 1586 in 600s
ta24js	1644 in 282s	1613 .. 1653 in 600s
ta25js	1543 .. 1608 in 600s	1531 .. 1619 in 600s
ta26js	1577 .. 1659 in 600s	1562 .. 1673 in 600s
ta27js	1639 .. 1691 in 600s	1627 .. 1702 in 600s
ta28js	1603 in 183s	1588 .. 1609 in 600s
ta29js	1553 .. 1635 in 600s	1537 .. 1644 in 600s
ta30js	1513 .. 1605 in 600s	1488 .. 1612 in 600s
ta31js	1764 .. 1766 in 600s	1764 .. 1768 in 600s
ta32js	1774 .. 1817 in 600s	1774 .. 1830 in 600s
ta33js	1774 .. 1824 in 600s	1783 .. 1857 in 600s
ta34js	1828 .. 1849 in 600s	1828 .. 1846 in 600s
ta35js	2007 in 2s	2007 in 11s
ta36js	1819 .. 1826 in 600s	1819 in 413s
ta37js	1771 .. 1796 in 600s	1771 .. 1812 in 600s
ta38js	1673 .. 1688 in 600s	1673 .. 1732 in 600s
ta39js	1795 in 51s	1795 in 506s
ta40js	1632 .. 1709 in 600s	1643 .. 1745 in 600s
ta41js	1858 .. 2073 in 600s	1890 .. 2100 in 600s
ta42js	1867 .. 1969 in 600s	1875 .. 1985 in 600s
ta43js	1809 .. 1890 in 600s	1809 .. 1941 in 600s
ta44js	1923 .. 2022 in 600s	1938 .. 2083 in 600s
ta45js	1991 .. 2016 in 600s	1997 .. 2042 in 600s
ta46js	1940 .. 2060 in 600s	1945 .. 2057 in 600s
ta47js	1782 .. 1936 in 600s	1800 .. 1986 in 600s
ta48js	1905 .. 1983 in 600s	1912 .. 2022 in 600s
ta49js	1903 .. 2016 in 600s	1927 .. 2051 in 600s
ta50js	1806 .. 1982 in 600s	1821 .. 2003 in 600s
ta51js	2760 in 6s	2760 in 329s
ta52js	2756 in 6s	2756 in 401s
ta53js	2717 in 2s	2717 in 104s
ta54js	2839 in 2s	2839 in 29s
ta55js	2679 in 10s	2679 .. 2693 in 600s
ta56js	2781 in 4s	2781 in 105s
ta57js	2943 in 2s	2943 in 60s
ta58js	2885 in 2s	2885 in 157s
ta59js	2655 in 7s	2655 .. 2682 in 600s
ta60js	2723 in 5s	2723 in 562s
ta61js	2868 in 8s	2868 .. 2916 in 600s
ta62js	2869 .. 2877 in 600s	2869 .. 3008 in 600s
ta63js	2755 in 45s	2755 .. 2825 in 600s
ta64js	2702 in 12s	2702 .. 2756 in 600s
ta65js	2725 in 30s	2725 .. 2842 in 600s
ta66js	2845 in 16s	2845 .. 2916 in 600s
ta67js	2825 .. 2826 in 600s	2825 .. 2869 in 600s
ta68js	2784 in 6s	2784 .. 2822 in 600s
ta69js	3071 in 7s	3071 in 286s
ta70js	2995 in 28s	2995 .. 3109 in 600s
ta71js	5464 in 17s	5464 .. 5648 in 600s
ta72js	5181 in 15s	5181 .. 5310 in 600s
ta73js	5568 in 17s	5568 .. 5648 in 600s
ta74js	5339 in 13s	5339 .. 5367 in 600s
ta75js	5392 in 31s	5392 .. 5693 in 600s
ta76js	5342 in 19s	5342 .. 5475 in 600s
ta77js	5436 in 11s	5436 .. 5488 in 600s
ta78js	5394 in 15s	5394 .. 5522 in 600s
ta79js	5358 in 21s	5358 .. 5463 in 600s
ta80js	5183 in 15s	5183 .. 5304 in 600s

YN instances

On an Windows PC with an i7 4-core 3.3GHz 32GB ram in 600 seconds

• OptalCP Demo Version 2025.7.0 with 1 FDS, 1 FDSLB, 2 LNS (2 provers, 2 searchers)
• CP-SAT V9.14.6206 with default configuration (its log reports running 8 workers)

Instance	OptalCP	CP-SAT
yn1	860 .. 884 in 600s	837 .. 889 in 600s
yn2	871 .. 914 in 600s	858 .. 917 in 600s
yn3	853 .. 903 in 600s	842 .. 918 in 600s
yn4	932 .. 977 in 600s	910 .. 985 in 600s

TAI 100 x 100 instances

On an Windows PC with an i7 4-core 3.3GHz 32GB ram in 600 seconds

• OptalCP Academic Version 2025.8.0 with 1 FDS, 3 LNS (1 prover, 3 searchers)
• CP-SAT V9.14.6206 with default configuration (its log reports running 8 workers)

Instance	OptalCP	CP-SAT
tai_j100_m100_1	62521 .. 79694 in 600s	62303 .. 89932 in 601s
tai_j100_m100_2	62741 .. 79265 in 600s	62032 .. 89636 in 601s
tai_j100_m100_3	61197 .. 78375 in 600s	60201 .. 89282 in 601s
tai_j100_m100_4	64449 .. 80653 in 600s	60980 .. 92178 in 601s
tai_j100_m100_5	61340 .. 79746 in 600s	61165 .. 90602 in 601s
tai_j100_m100_6	60932 .. 79567 in 600s	59272 .. 92399 in 601s
tai_j100_m100_7	63641 .. 78857 in 600s	62755 .. 90905 in 601s
tai_j100_m100_8	62989 .. 79131 in 600s	61238 .. 90028 in 601s
tai_j100_m100_9	62379 .. 80599 in 600s	60619 .. 92256 in 601s
tai_j100_m100_10	64866 .. 79005 in 600s	61008 .. 90217 in 601s