Coverage for moptipy/examples/jssp/__init_

1"""

2The Job Shop Scheduling Problem is a good example for optimization tasks.

4The JSSP is one of the most well-known combinatorial optimization tasks.

5Here we provide the well-known and often-used set of benchmark instances

6(:mod:`~moptipy.examples.jssp.instance`) for this problem. Moreover, we

7also run a fully-fledged example experiment applying many metaheuristics

8to eight selected JSSP instances in module

9:mod:`~moptipy.examples.jssp.experiment` and evaluate the data gathered from

10this experiment in :mod:`~moptipy.examples.jssp.evaluation`. Be aware that

11actually executing this experiment will take a very long time. However, you

12can also find the complete experiment, every single algorithm used, and all

13conclusions drawn with in-depth discussions in our online book "Optimization

14Algorithms" at https://thomasweise.github.io/oa.

16Anyway, here you have many JSSP benchmark instances, a useful search space,

17and the common objective function. You can use them for your own research, if

18you want: The JSSP benchmark instances can be loaded from a package-internal

19resource by name using module :mod:`~moptipy.examples.jssp.instance`.

20Solutions to a JSSP instances are :class:`~moptipy.examples.jssp.gantt.Gantt`

21charts, i.e., diagrams which assign each operation of a job to a machine and

22time slot. The :class:`~moptipy.examples.jssp.gantt_space.GanttSpace` is a

23space operating on such charts and the

24:class:`~moptipy.examples.jssp.makespan.Makespan` is the typical objective

25function when solving JSSPs. Gantt charts can be encoded as permutations

26with repetitions using the :mod:`~moptipy.examples.jssp.ob_encoding`.

281. Ronald Lewis Graham, Eugene Leighton Lawler, Jan Karel Lenstra, Alexander

29 Hendrik George Rinnooy Kan. Optimization and Approximation in Deterministic

30 Sequencing and Scheduling: A Survey. *Annals of Discrete Mathematics*

31 5:287-326, 1979. doi: https://doi.org/10.1016/S0167-5060(08)70356-X.

32 https://ir.cwi.nl/pub/18052/18052A.pdf.

332. Eugene Leighton Lawler, Jan Karel Lenstra, Alexander Hendrik George Rinnooy

34 Kan, and David B. Shmoys. Sequencing and Scheduling: Algorithms and

35 Complexity. Chapter 9 in Stephen C. Graves, Alexander Hendrik George

36 Rinnooy Kan, and Paul H. Zipkin, editors, *Handbook of Operations Research

37 and Management Science,* volume IV: *Production Planning and Inventory,*

38 1993, pages 445-522. Amsterdam, The Netherlands: North-Holland Scientific

39 Publishers Ltd. doi: https://doi.org/10.1016/S0927-0507(05)80189-6.

40 http://alexandria.tue.nl/repository/books/339776.pdf.

413. Eugene Leighton Lawler. Recent Results in the Theory of Machine Scheduling.

42 Chapter 8 in Achim Bachem, Bernhard Korte, and Martin Grötschel, editors,

43 *Math Programming: The State of the Art,* 1982, pages 202-234.

44 Bonn, Germany/New York, NY, USA: Springer-Verlag GmbH.

45 ISBN: 978-3-642-68876-8. doi: https://doi.org/10.1007/978-3-642-68874-4_9.

464. Éric D. Taillard. Benchmarks for Basic Scheduling Problems. *European

47 Journal of Operational Research (EJOR)* 64(2):278-285, January 1993.

48 doi: https://doi.org/10.1016/0377-2217(93)90182-M.

49 http://mistic.heig-vd.ch/taillard/articles.dir/Taillard1993EJOR.pdf.

505. Jacek Błażewicz, Wolfgang Domschke, and Erwin Pesch. The Job Shop

51 Scheduling Problem: Conventional and New Solution Techniques. *European

52 Journal of Operational Research (EJOR)* 93(1):1-33, August 1996.

53 doi: https://doi.org/10.1016/0377-2217(95)00362-2.

546. Thomas Weise. *Optimization Algorithms.* 2021-2023. Hefei, Anhui, China:

55 Institute of Applied Optimization, School of Artificial Intelligence and

56 Big Data, Hefei University. https://thomasweise.github.io/oa

57"""

60def __lang_setup() -> None:

61 """Perform the language setup."""

62 from moptipy.utils.lang import DE, EN, ZH # pylint: disable=C0415 # noqa

64 # the English language strings

65 EN.extend({

66 "gantt_info": "{gantt.instance.name} ({gantt.instance.jobs} "

67 "jobs \u00D7 {gantt.instance.machines} machines), "

68 "makespan {gantt[:,:,2].max()}",

69 "gantt_info_no_ms": "{gantt.instance.name} ({gantt.instance.jobs} "

70 "jobs \u00D7 {gantt.instance.machines} machines)",

71 "gantt_info_short": "{gantt.instance.name} / {gantt[:,:,2].max()}",

72 "machine": "machine",

73 "makespan": "makespan",

74 })

75 # the German language strings

76 DE.extend({

77 "gantt_info": "{gantt.instance.name} ({gantt.instance.jobs} "

78 "Jobs \u00D7 {gantt.instance.machines} Maschinen), "

79 "Makespan {gantt[:,:,2].max()}",

80 "gantt_info_no_ms": "{gantt.instance.name} ({gantt.instance.jobs} "

81 "Jobs \u00D7 {gantt.instance.machines} Maschinen)",

82 "gantt_info_short": "{gantt.instance.name} / {gantt[:,:,2].max()}",

83 "machine": "Maschine",

84 "makespan": "Makespan",

85 })

86 # the Chinese language strings

87 ZH.extend({

88 "gantt_info": "{gantt.instance.name} ({gantt.instance.jobs}份作业"

89 "\u00D7{gantt.instance.machines}台机器), "

90 "最大完工时间{gantt[:,:,2].max()}",

91 "gantt_info_no_ms":

92 "{gantt.instance.name} ({gantt.instance.jobs}份作业"

93 "\u00D7{gantt.instance.machines}台机器) ",

94 "gantt_info_short": "{gantt.instance.name} / {gantt[:,:,2].max()}",

95 "machine": "机器",

96 "makespan": "最大完工时间",

97 })

100__lang_setup() # invoke the language setup

101del __lang_setup # delete the language setup routine

Coverage for moptipy / examples / jssp / init.py: 100%

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