Page - 95 - in Algorithms for Scheduling Problems

Algorithms 2018,11, 68 15. May,G.; Stahl, B.; Taisch,M.; Prabhu,V.Multi-objectivegenetic algorithm for energy-efficient job shop scheduling. Int. J.Prod. Res. 2015,53, 7071–7089. [CrossRef] 16. Zhang,R.;Chiong,R.Solvingtheenergy-efficient jobshopschedulingproblem:Amulti-objectivegenetic algorithm with enhanced local search for minimizing the total weighted tardiness and total energy consumption. J.Clean. Prod. 2016,112, 3361–3375. [CrossRef] 17. Mouzon,G.;Yildirim,M.B.;Twomey, J.Operationalmethodsforminimizationofenergyconsumptionof manufacturingequipment. Int. J.Prod. Res. 2007,45, 4247–4271. [CrossRef] 18. Dai,M.;Tang,D.;Giret,A.;Salido,M.A.;Li,W.D.Energy-efficient schedulingforaflexibleflowshopusing an improvedgenetic-simulated annealing algorithm. Robot. Comput. Integr. Manuf. 2013, 29, 418–429. [CrossRef] 19. Mansouri, S.A.; Aktas, E.; Besikci,U.Green schedulingof a two-machineflowshop: Trade-off between makespanandenergyconsumption.Eur. J.Oper. Res. 2016,248, 772–788. [CrossRef] 20. Hecker,F.T.;Hussein,W.B.;Paquet-Durand,O.;Hussein,M.A.;Becker,T.Acasestudyonusingevolutionary algorithmstooptimizebakeryproductionplanning.ExpertSyst.Appl. 2013,40, 6837–6847. [CrossRef] 21. Hecker,F.T.; Stanke,M.;Becker,T.;Hitzmann,B.ApplicationofamodifiedGA,ACOandarandomsearch procedure tosolve theproductionschedulingofacasestudybakery.ExpertSyst.Appl. 2014,41, 5882–5891. [CrossRef] 22. Fonseca, C.M.; Fleming, P.J. An overview of evolutionary algorithms in multiobjective optimization. Evol.Comput. 1995,3, 1–16. [CrossRef] 23. Hosseinabadi,A.A.R.; Siar,H.; Shamshirband, S.; Shojafar,M.;Nasir,M.H.N.M.Using thegravitational emulation local searchalgorithmtosolve themulti-objectiveflexibledynamic jobshopschedulingproblem inSmallandMediumEnterprises.Ann.Oper. Res. 2015,229, 451–474. [CrossRef] 24. Deb,K.;Pratap,A.;Agarwal,S.;Meyarivan,T.Afastandelitistmultiobjectivegeneticalgorithm:NSGA-II. IEEETrans. Evol. Comput. 2002,6, 182–197. [CrossRef] 25. Jaimes,A.L.;Coello,C.A.C. InteractiveApproachesApplied toMultiobjectiveEvolutionaryAlgorithms. InMulticriteriaDecisionAidandArtificial Intelligence;Doumpos,M.,Grigoroudis,E.,Eds.; JohnWiley&Sons, Ltd.: Chichester,UK,2013. [CrossRef] 26. Lu,L.;Anderson-Cook,C.;Lin,D.Optimaldesignedexperimentsusingapareto frontsearchfor focused preferenceofmultipleobjectives.Comput. Stat.DataAnal. 2014,71, 1178–1192. [CrossRef] 27. Wagner,T.;Trautmann,H. Integrationofpreferences inhypervolume-basedmultiobjectiveevolutionary algorithmsbymeansofdesirability functions. IEEETrans. Evol. Comput. 2010,14, 688–701. [CrossRef] 28. Baker,K.R. Introduction toSequencingandScheduling; JohnWiley&Sons,Ltd.:NewYork,NY,USA,1974. 29. Pinedo,M.Scheduling: Theory,Algorithms, andSystems;PrenticeHall:UpperSaddleRiver,NJ,USA,2002; 586p. 30. Abyaneh,S.H.;Zandieh,M.Bi-objectivehybridflowshopschedulingwithsequence-dependentsetuptimes andlimitedbuffers. Int. J.Adv.Manuf. Technol. 2012,58, 309–325. [CrossRef] 31. Graham,R.L.;Lawler,E.L.;Lenstra, J.K.;Kan,A.H.G.R.Optimizationandapproximation indeterministic sequencingandscheduling:Asurvey.Ann.Discret.Math. 1979,5, 287–326. [CrossRef] 32. Larrañaga,P.;Kuijpers,C.M.H.;Murga,R.H.; Inza, I.;Dizdarevic,S.Geneticalgorithmsfor the travelling salesmanproblem:Areviewofrepresentationsandoperators.Artif. Intell. Rev. 1999,13, 129–170. [CrossRef] 33. Tan,K.C.;Lee,L.H.;Zhu,Q.L.;Ou,K.Heuristicmethods forvehicle routingproblemwith timewindows. Artif. Intell. Eng. 2001,15, 281–295. [CrossRef] 34. Gog,A.; Chira,C.ComparativeAnalysis of RecombinationOperators inGeneticAlgorithms for the Travelling SalesmanProblem; Springer: Berlin/Heidelberg,Germany,2011;pp.10–17. 35. Hwang,H.Animprovedmodel forvehicleroutingproblemwithtimeconstraintbasedongeneticalgorithm. Comput. Ind. Eng. 2002,42, 361–369. [CrossRef] 36. Prins,C.Asimpleandeffectiveevolutionaryalgorithmfor thevehicle routingproblem.Comput.Oper. Res. 2004,31, 1985–2002. [CrossRef] 37. Starkweather,T.;McDaniel, S.;Mathias,K.E.;Whitley,C.Acomparisonofgenetic sequencingoperators. InProceedingsof the4thInternationalConferenceonGeneticAlgorithms;Belew,R.K.,Booker,L.B.,Eds.; MorganKaufmann: SanFrancisco,CA,USA,1991;pp.69–76. 38. TheRProject forStatisticalComputing.Availableonline: https://www.r-project.org/(accessedon4March 2017). 95