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Algorithms 2018,11, 50 Figure3.Permutationsofcompetingoperations inbranch-and-boundalgorithm. 2.3.2.Gradient-AlikeAlgorithm Theoppositeof thementionedaboveapproachwouldbesearchingfora localminimumamong all combinationswithagradientalgorithm[11].Here,wewill computeananalogueof thederivative that isusedtodefinethesearchdirectionateachpoint [12]. ‘Derivative’ foreachcompetingoperation is calculatedby trying to shift it byoneposition to the left. In case theobjective function reduces (or increases formaximization problems)we shift the operation to the leftwith the defined step (thestepratio ismeasured inanumberofpositionoperationskipsmoving to the left). The formal presentationof thedesignedgradient-alikealgorithmisdescribedbyProcedure2. Procedure2: gradientalgorithm 1.FindtheinitialsolutionoftheLPproblem (1)–(3)forthecombinationck∈{0,1},k=1,. . . ,K thatcorresponds to thecasewhenallordersare inarow(firstoperationof the followingorderstarts onlyafter the lastoperationofprecedingorder iscompleted). 2.Remember thesolutionandkeepthevalueofobjective functionΦas temporarilybest result Opt=Φ. 3.Select the lastorder f= |F|. 4.Select the resource r= |R| that isusedbyfirstoperation i= 1of thesequencegraphof the manufacturingprocess. 5. The current optimization variable for gradient optimization is selected—position of operation iof theorder f ontheresource r< i,r, f>. 6.Condition:Does theselectedresource rhavemorethanoneoperation inthemanufacturing procedure thatallocates it? 6.1. Ifyes then Beginoptimizingposition< i,r, f> 6.1.1.Set thestepofshifting theoperation tomaximum(shifting to the leftmostposition). D(i,r, f)=max 6.1.2.Findthe ‘derivative’ofshifting theoperation i to the left Shift theoperation ionepositionto the left Find thesolutionof theLPproblem (1)–(3) forcurrentcombinationandcalculate the objective functionΦ ConditionA: is thesolutionfeasible? If feasible then ConditionB: Is theobjectivefunctionvalueΦbetter thantemporarilybest resultOpt? Ifyes then Wefoundtheoptimizationdirectionforposition< i,r, f>,proceedtop. 6.1.3 Ifnot then 120
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Algorithms for Scheduling Problems
Titel
Algorithms for Scheduling Problems
Autoren
Frank Werner
Larysa Burtseva
Yuri Sotskov
Herausgeber
MDPI
Ort
Basel
Datum
2018
Sprache
englisch
Lizenz
CC BY 4.0
ISBN
978-3-03897-120-7
Abmessungen
17.0 x 24.4 cm
Seiten
212
Schlagwörter
Scheduling Problems in Logistics, Transport, Timetabling, Sports, Healthcare, Engineering, Energy Management
Kategorien
Informatik
Technik
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Algorithms for Scheduling Problems