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Algorithms 2018,11, 68 of tasks;eachset isassignedaprocessingorder (Proc.Order). Thesesetsare formedaccordingto the processingcompatibility. ݉ͳ ݉ʹ Ordered 1 2 1 2 Proc. Order 2 3 13 15 5 6 7 8 1 4 9 10 11 12 14 16 Batch 1 4 2 1 3 4 Jobs Figure7.Chromosomerepresentationexamplewith twomachinesperstage. ݉ͳ ݉ʹ ݉͵ ݉Ͷ Ordered 1 2 1 1 Proc. Order 2 3 6 7 3 15 5 8 10 11 12 16 1 4 9 14 Batch 1 4 2 1 4 2 3 4 1 3 4 Jobs Figure8.Chromosomerepresentationexamplewith fourmachinesperstage. The tasksof Jobs1,3,and4canbeprocessed in thesamesetat thesametime. Thetasksof Job2 areput intoaseparatesetbecause theyarenotcompatiblewitheachother. Forexample, inFigure7, the first two tasks (1-1, 4-1) are processed byMachine 1, then the second setwith one task (2-1). InMachine2, twotasksof thefirst set (1-2and3-1)areprocessed,assumingthat themachinehasonly thecapacity toprocessupto6batches (60kg). Thesecondsetwill thenbefollowedbyonetask (4-1). Figure8showsfourmachinesperstage. Fourbatchesareassignedtoeachmachine.Machines1 and2process twosetsof tasks.Machines3and4processonlyoneset.Uponcompletionof the tasks processed insets inStep1, in the laterstages, theywillbeprocessed individually. Ordercrossover (OX) [32,34–37]: Twocutpointsareselectedrandomly; thepartof thefirstparent locatedbetween these twocutpoints is copied to the child. Thechild’sother spacesare left blank. Thevaluescopiedto thechildaredeleted inthesecondparent. Thefollowingpositions in thechild arefilledstarting in theblankspacesandconsideringtheorder foundin thesecondparent (Figure9). Figure9.Ordercrossover (OX)operator. 5.3.MutationOperators Mutationoperatorsproducesmallchanges inindividualsaccordingtoaprobability. Thisoperator helps to prevent falling into local optima and to extend the search space of the algorithm. Three mutationoperatorsareconsidered:Displacement,Exchange,andInsertion. Displacement isageneralizationof the insertionmutation, inwhich insteadofmovingasingle value, severalvaluesarechanged(Figure10). Theexchangeoperatorselects tworandompointsand thesepositionvaluesareexchanged(Figure11). In insertion,avalue is selectedrandomlyandwillbe insertedatanarbitraryposition(Figure12). 83
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Algorithms for Scheduling Problems
Title
Algorithms for Scheduling Problems
Authors
Frank Werner
Larysa Burtseva
Yuri Sotskov
Editor
MDPI
Location
Basel
Date
2018
Language
English
License
CC BY 4.0
ISBN
978-3-03897-120-7
Size
17.0 x 24.4 cm
Pages
212
Keywords
Scheduling Problems in Logistics, Transport, Timetabling, Sports, Healthcare, Engineering, Energy Management
Categories
Informatik
Technik
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Algorithms for Scheduling Problems