Abstract
Since multi-objective flow shop scheduling problem (MFSP) plays a key role in practical scheduling, there has been an increasing interest in MFSP according to the literature. However, there still have been wide gaps between theories and practical applications, and the review research of multi-objective optimization algorithms in MFSP (objectives > 2) field is relatively scarce. In view of this, this paper provides a comprehensive review of both former and the state-of-the-art approaches on MFSP. Firstly, we introduce a broad description and the complexity of MFSP. Secondly, a taxonomy of multi-objective optimizations and an analysis of the publications on MFSP are presented. It is noteworthy that heuristic and meta-heuristic methods and hybrid procedures are proven much more useful than other methods in large and complex situations. Finally, future research trends and challenges in this field are proposed and analyzed. Our survey shows that algorithms developed for MFSP continues to attract significant research interest from both theoretical and practical perspectives.
Similar content being viewed by others
References
Shi RF (2008) Current progress in evolutionary algorithm based multi-objective production scheduling. Journal of Jishou University (Natural Science Edition) 29(6):42–46 (in Chinese)
Nagar A, Heragu SS, Haddock J (1995) Mutiple and bi-criteria scheduling: a literature survey. Eur J Oper Res 81:88–104
T’kindt V, Billaut JC (2001) Multicriteria scheduling problems: a survey. Rairo Oper Res 35:143–163
Jones DF, Mirrazavi SK, Tamiz M (2002) Multiobjective metaheuristics: an overview of the current state-of-the-art. Eur J Oper Res 137:1–94
Hoogeveen H (2005) Multicriteria scheduling. Eur J Oper Res 167:592–623
Minella G, Ruiz R, Ciavotta M (2008) A review and evaluation of multiobjective algorithms for the flowshop scheduling problem. Informs J Comput 20(3):451–471
Pinedo ML (2008) Scheduling: theory, algorithm, and systems, 3rd edn. Springer, Berlin
Graham RL, Lawler EL, Lenstra JK, Rinnooy Kan AHG (1979) Optimization and approximation in deterministic sequencing and scheduling: a survey. Ann Discrete Math 5:287–326
Garey MR, Johnson DS, Sethi R (1976) The complexity of flowshop and job shop scheduling. Math Oper Res 1:117–129
Gonzalez T, Sahni S (1978) Flowshop and jobshop schedules: complexity and approximation. Oper Res 26:36–52
Du J, Leung JYT (1990) Minimizing total tardiness on one machine is NP-hard. Math Oper Res 15:483–495
T’kindt V, BILLANT J (2005) Multicriteria scheduling: theory models and algorithms [M], 2nd edn. Springer, Berlin
Carlos Coello, Gary Lamont, David Veldhuizen (2007) Evolutionary algorithms for solving multi-objective problems, 2nd edn, vol 2. Springer, New York, pp 5–60
Fourman MP (1985) Compaction of symbolic layout using genetic algorithms. In: Grefenstette JJ (ed) Genetic and algorithms and their applications: Proceedings of the First International Conference on Genetic Algorithms. Lawrence Erlbaum, Hillsdale, pp 141–153
T’kindt V, Gupta JND, Billaut JC (2003) Two-machine flowshop scheduling with a secondary criterion. Comput Oper Res 30:505–526
Gupta JND, Neppalli VR, Werner F (2001) Minimizing total flow time in a two-machine flowshop problem with minimum makespan. Int J Prod Econ 69:323–338
Lemesre J, Dhaenens C, Talbi EG (2007) An exact parallel method for a biobjective permutation flowshop problem. Eur J Oper Res 177:1641–1655
Naderi B, Zandieh M, Balagh AKG, Roshanaei V (2009) An improved simulated annealing for hybrid flowshops with sequence-dependent setup and transportation times to minimize total completion time and total tardiness. Expert Syst Appl 36:9625–9633
Eren T, Güner E (2006) A bi-criteria flowshop scheduling problem with setup time. Appl Math Comput 183:1292–1300
T’kindt V, Monmarche N, Tercinet F, Laugt D (2002) An ant colony optimization algorithm to solve a 2-machine bi-criteria flowshop scheduling problem. Eur J Oper Res 142:250–257
Tseng CT, Liao CJ (2008) A discrete particle swarm optimization for lot-streaming flowshop scheduling problem. Eur J Oper Res 191:360–373
Ravindran D, Haq AN, Selvakuar SJ, Sivaraman R (2005) Flow shop scheduling with multiple objective of minimizing makespan and total flow time. Int J Adv Manuf Technol 25:1007–1012
Murata T, Ishibuchi H, Tanaka H (1996) Multiobjective genetic algorithm and its applications to flowshop scheduling. Comput Ind Eng 30:957–968
Nagar A, Heragu SS, Haddock J (1995) A branch-and-bound approach for a two-machine flowshop scheduling problem. J Oper Res Soc 46:721–734
Ishibuchi H, Murata T (1998) A multiobjective genetic local search algorithm and its application to flowshop scheduling. IEEE Trans Syst Man Cybern C 28(3):392–403
Qian B, Wang L, Huang DX, Wang X (2006) Multi-objective flow shop scheduling using differential evolution. Lect Notes Control Inf 345:1125–1136
Tavakkoli-Moghaddam R, Rahimi-Vahed A, Mirzaei AH (2007) A hybrid multi-objective immune algorithm for a flow shop scheduling problem with bi-objectives: weighted mean completion time and weighted mean tardiness. Inf Sci 177:5072–5090
Shi RF (2006) Current progress in evolutionary algorithm based multi-objective production scheduling. Journal of Jishou University (Natural Science Edition) 29(6):42–46 (in Chinese)
Brintrup AM, Ramsden J, Tiwari A (2007) An interactive genetic algorithm-based framework for handling qualitative criteria in design optimization. Comput Ind 58:279–291
Tantar E, Dhaenens C, Figueira JR, Talbi EG (2008) A priori landscape analysis in guiding interactive multi-objective metaheuristics. CEC (IEEE World Congress on Computational Intelligence), pp 4104–4111
Kuo CC (2009) Capacitor placement and scheduling using interactive bi-objective programming with valuable trade off approach. Energ Convers Manage 50:995–1003
Land AH, Doig AG (1960) An automatic method for solving discrete programming problems. The Econometric Society 28(3):497–520
Liao CJ, Yu WC, Joe CB (1997) Bicriterion scheduling in the two-machine flowshop. J Oper Res Soc 48:929–935
Sivrikaya-Serifoğlu F, Ulusoy G (1998) A bicriteria two-machine permutation flowshop problem. Eur J Oper Res 107:414–430
Sayın S, Karabatı S (1999) A bicriteria approach to the two machine flow shop scheduling problem. Eur J Oper Res 113:435–449
Yeh WC (1999) A new branch-and-bound approach for the n/2/flowshop/αF+βC max flowshop scheduling problem. Comput Oper Res 26:1293–1310
Lee WC, Wu CC (2001) Minimizing the total flow time and the tardiness in a two-machine flow shop. Int J Syst Sci 32:365–373
Yeh WC (2001) An efficient branch-and-bound algorithm for the two-machine bi-criteria flowshop scheduling problem. J Manuf Syst 20:113–123
Lin BMT, Wu JM (2006) Bi-criteria scheduling in a two-machine permutation flowshop. Int J Prod Res 44:2299–2312
Metropolis N, Rosenblatt AW, Rosenblatt MN, Teller AH, Teller E (1953) Equation of state calculation by fast computing machines. J Chem Phys 21(6):1087–1092
Kirkpatrick S, Gelatt C, Vecchi P (1983) Optimization by simulated annealing. Science 220:671–679
Cerny V (1985) Thermodynamics approach to the traveling salesman problem: an efficient simulation algorithm. J Optimiz Theory App 45:41–51
Suresh RK, Mohanasundaram KM (2004) Pareto archived simulated annealing for permutation flow shop scheduling with multiple objectives. Proceedings of IEEE Conference on Cybernetics and Intelligent Systems (CIS), vol 2. Singapore, December 1–3, pp 712–717
Loukil T, Teghem J, Tuyttens D (2005) Solving multiobjective production scheduling problems using metaheuristics. Eur J Oper Res 161:42–61
Varadharajan TK, Rajendran C (2005) A multiobjective simulated annealing algorithm for scheduling in flowshops to minimize the makespan and total flow time of jobs. Eur J Oper Res 167:772–795
Hatami S, Ebrahimnejad S, Tavakkoli-Moghaddam R, Maboudian Y (2010) Two meta-heuristics for three-stage assembly flowshop scheduling with sequence-dependent setup times. Int J Adv Manuf Technol 50:1153–1164
Glover F (1986) Future paths for integer programming and links to artificial intelligence. Comput Oper 13(5):533–549
Loukil T, Teghem J, Fortemps P (2000) Solving multiobjective production scheduling problems with tabu search. Control Cybern 29(3):819–828
Armentano VA, Arroyo JEC (2004) An application of a multiobjective tabu search algorithm to a bi-criteria flowshop problem. J Heuristics 10:463–481
Eren T, Güner E (2008) A bi-criteria flowshop scheduling with a learning effect. Appl Math Comput 32(9):1719–1733
Eren T, Güner E (2008) The triceiteria flowshop scheduling problem. Int J Adv Manuf Technol 36:1210–1220
Holland JH (1975) Adaptation in natural and artificial systems. University of Michigan Press, Ann Arbor
Neppalli VR, Chen CL, Gupta JND (1996) Genetic algorithms for the two-stage bi-criteria flowshop problem. Eur J Oper Res 95:356–373
Murata T, Ishibuchi H, Gen M (2001) Specification of genetic search directions in cellular multiobjective genetic algorithms. In: Zitzler E, Deb K, Thiele L, Coello Coello CA, Corne D (eds) First International Conference on Evolutionary Multi-Criterion Optimization. Springer, Lecture Notes in Computer Science No. 1993, pp 82–95
Bagchi TP (2001) Pareto-optimal solutions for multiobjective production scheduling problems. In: Zitzler E, Deb K, Thiele L, Coello Coello CA, Corne D (eds) First International Conference on Evolutionary Multi-Criterion Optimization. Springer, Lecture Notes in Computer Science No. 1993, pp 458–471
Chang PC, Hsieh JC, Lin SG (2002) The development of gradual-priority weighting approach for the multiobjective flowshop scheduling problem. Int J Prod Econ 79:171–183
Dugardin F, Yalaoui F, Amodeo L (2010) New multi-objective method to solve reentrant hybrid flow shop scheduling problem. Eur J Oper Res 203:22–31
Karimi N, Zandieh M, Karamooz HR (2010) Bi-objective group scheduling in hybrid flexible flowshop: a multi-phase approach. Expert Syst Appl 37:4024–4032
Sridhar J, Rajendran C (1996) Scheduling in flowshop and cellular manufacturing systems with multiple objectives: a genetic algorithmic approach. Prod Plan Control 7:374–382
Cavalieri S, Gaiardelli P (1998) Hybrid genetic algorithms for a multiple-objective scheduling problem. J Intell Manuf 9:361–367
Yeh WC (2002) A memetic algorithm for the n/2/flowshop/αF+βC max scheduling problem. Int J Adv Manuf Technol 20:464–473
Ishibuchi H, Yoshida T, Murata T (2003) Balance between genetic search and local search in memetic algorithms for multiobjective permutation flowshop scheduling. IEEE Trans Evol Comput 7:204–223
Ponnambalam SG, Jagannathan H, Kataria M, Gadicherla A (2004) A TSP-GA multiobjective algorithm for flow-shop scheduling. Int J Adv Manuf Technol 23:909–915
Arroyo JEC, Armentano VA (2005) Genetic local search for multiobjective flowshop scheduling problems. Eur J Oper Res 167:717–738
Pasupathy T, Rajendran C, Suresh RK (2006) A multiobjective genetic algorithm for scheduling in flow shops to minimize the makespan and total flow time of jobs. Int J Adv Manuf Technol 27:804–815
Melab N, Mezmaz M, Talbi EG (2006) Parallel cooperative meta-heuristics on the computational grid. A case study: the biobjective flow-shop problem. Parallel Comput 32:643–659
Li BB, Wang L (2007) A hybrid quantum-inspired genetic algorithm for multi-objective flow shop scheduling. IEEE Trans Syst Man Cybern B 37:576–591
Chang PC, Chen SH, Liu CH (2007) Sub-population genetic algorithm with mining gene structures for multi-objective flow shop scheduling problems. Expert Syst Appl 33:762–771
Dorigo M (1992) Optimization, learning and natural algorithms. Dissertation, Dipartimento di Elettronica, Politecnico di Milano, Italy (in Italian)
Dorigo M, Maniezzo V, Colorni A (1996) The ant system: optimization by a colony of cooperating agents. IEEE Trans Syst Man Cybern B 26:29–41
Rajendran C, Ziegler H (2004) Ant-colony algorithms for permutation flow shop scheduling to minimize makespan/total flow time of jobs. Eur J Oper Res 155:426–438
Stuetzle T (1998) An ant approach for the flow shop problem. Proceedings of the 6th European Congress on Intelligent Techniques and Soft Computing (EUFIT_98), vol 3. Verlag Mainz, Aachen, Germany, pp 1560–1564
Merkle D, Middendorf M (2000) An ant algorithm with a new pheromone evaluation rule for total tardiness problems. Proceedings of the EvoWorkshops. Lecture Notes in Computer Science, vol 1803). Springer, Berlin, pp 287–296
Pasia JM, Hartl RF, Doerner KF (2006) Solving a bi-objective flowshop scheduling problem by Pareto-ant colony optimization. In: Dorigo M, Gambardella LM, Birattari M, Martinoli A, Poli R, Stützle T (eds) Lecture Notes in Computer Science, vol 4150. Ant Colony Optimization and Swarm Intelligence, pp 294–305
Yagmahan B, Yenisey MM (2008) Ant colony optimization for multi-objective flow shop scheduling problem. Comput Ind Eng 54:411–420
Marimuthu S, Ponnambalamb SG, Jawahar N (2009) Threshold accepting and ant-colony optimization algorithms for scheduling m-machine flow shops with lot streaming. J Mater Process Technol 209:1026–1041
Huang RH, Yang CL (2009) Solving a multi-objective overlapping flow-shop scheduling. Int J Adv Manuf Technol 42:955–962
Yagmahan B, Yenisey MM (2010) A multi-objective ant colony system algorithm for flow shop scheduling problem. Expert Syst Appl 37:1361–1368
Kennedy J, Eberhart RC (1995) Particle swarm optimization. Proceedings of IEEE International Conference on Neural Networks, 4. IEEE Service Center, Piscataway, NJ, pp 1942–1948
Kennedy J, Eberhart RC, Shi Y (2001) Swarm intelligence. Morgan Kaufmann, San Francisco
Guo WZ, Chen GL, Huang M, Chen SL (2007) A discrete particle swarm optimization algorithm for the multi-objective permutation flow shop sequencing problem. Proceeding of International Conference on Fuzzy Information and Engineering, pp 323–331
Rahimi-Vahed AR, Mirghorbani SM (2007) A multiobjective particle swarm for a flow shop scheduling problem. J Comb Optim 13:79–102
Li BB, Wang L, Liu B (2008) An effective PSO-based hybrid algorithm for multiobjective permutation flow shop scheduling. IEEE Trans Syst Man Cybern A38(4):818–831
Liao CJ, Tseng CT, Luarn P (2007) A discrete version of particle swarm optimization for flowshop scheduling problems. Comput Oper Res 34:3099–3111
Sha DY, Lin HH (2009) A particle swarm optimization for multi-objective flowshop scheduling. Int J Adv Manuf Technol 45:749–758
Storn R, Price K (1997) Differential evolution—a simple and efficient adaptive scheme for global optimization over continuous spaces. J Glob Optim 11:341–59
Qian B, Wang L, Huang DX, Wang X (2009) Mutli-objective no-wait flow-shop scheduling with a memetic algorithm based on differential evolution. Soft Comput 13:847–869
Qian B, Wang L, Huang DX, Wang WL, Wang X (2009) An effective hybrid DE-based algorithm for multi-objective flow shop scheduling with limited buffers. Comput Oper Res 36:209–233
Pan QK, Wang L, Qian B (2009) A novel differential evolution algorithm for bi-criteria no-wait flow shop scheduling problems. Comput Oper Res 36:2498–2511
Zheng TM, Yamashiro M (2010) Solving flow shop scheduling problems by quantum differential evolutionary algorithm. Int J Adv Manuf Technol 49:643–662
Forrest S, Javornik B, Smith R, Perelson AS (1993) Using genetic algorithms to explore pattern recognition in the immune system. Evol Comput 1(3):191–211
Yang JG, Ding HM, Li P (2002) An immune scheduling algorithm for solving multi-objective flow-shop problem. Mach Des Res 18(4):28–31 (in Chinese)
Tavakkoli-Moghaddam R, Rahimi-Vahed A, Mirzaei AH (2008) Solving a multi-objective no-wait flow shop scheduling problem with an immune algorithm. Int J Adv Manuf Technol 36:969–981
Chakhlevitch K, Cowling P (2006) Hyperheuristics: recent developments. In: Cotta C, Sevaux M, and Sörensen K (eds) Adaptive and multilevel metaheuristics, studies in computational intelligence, 136. Springer 2008, pp 3–29
Rajendran C (1995) Heuristics for scheduling in flowshop with multiple objectives. Eur J Oper Res 82:540–555
Ho JC, Chang YL (1991) A new heuristic for the n-job, M-machine flow-shop problem. Eur J Oper Res 52:194–202
Framinan JM, Leisten R, Ruiz-Usano R (2002) Efficient heuristics for flowshop sequencing with the objectives of makespan and flow time minimisation. Eur J Oper Res 141:559–569
Allahverdi A (2003) The two- and m-machine flowshop scheduling problems with bi-criteria of makespan and mean flow time. Eur J Oper Res 147:373–396
Allahverdi A (2004) A new heuristic for m-machine flowshop scheduling problem with bi-criteria of makespan and maximum tardiness. Comput Oper Res 31:157–180
Arroyo JEC, Armentano VA (2004) A partial enumeration heuristic for multiobjective flowshop scheduling problems. J Oper Res Soc 55:1000–1007
Framinan JM, Leisten R (2006) A heuristic for scheduling a permutation flowshop with makespan objective subject to maximum tardiness. Int J Prod Econ 99:28–40
Gupta JND, Hennig K, Werner F (2002) Local search heuristics for two-stage flow shop problems with secondary criterion. Comput Oper Res 29:123–149
Geiger MJ (2007) On operators and search space topology in multiobjective flow shop scheduling. Eur J Oper Res 181:195–206
Haq AN, Ramanan TR (2006) A bi-criterian flow shop scheduling using artificial neural network. Int J Adv Manuf Technol 30:1132–1138
Shi RF, Zhou H (2007) Escalating evolutionary algorithm with application to bi-objective flow shop scheduling problems. J Manage Sci 10(5):11–20 (in Chinese)
Zhang CK, Li XF, Shao HH, Ren DX (2002) Bi-directional simulation approach for multi-objective scheduling problem of hybrid flow shop. J Shanghai Jiaotong Univ 36(4):547–550 (in Chinese)
Wei Z, Xu XF, Deng SC (2006) Evolutionary algorithm for solving multi-objective hybrid flow-shop scheduling problem. Journal of Nanjing University of Science and Technology 30(3):327–331 (in Chinese)
Behnamian J, Fatemi Ghomi SMT, Zandieh M (2009) A multi-phase covering Pareto-optimal front method to multi-objective scheduling in a realistic hybrid flowshop using a hybrid metaheuristic. Expert Syst Appl 36:11057–11069
Figueira JR, Liefooghe A, Talbi EG, Wierzbicki AP (2010) A parallel multiple reference point approach for multi-objective optimization. Eur J Oper Res 205:390–400
Sawik T (2007) A lexicographic approach to bi-objective scheduling of single- period orders in make-to-order manufacturing. Eur J Oper Res 180(3):1060–1075
Janiak A, Kozan E, Lichtenstein M, Oguz C (2007) Metaheuristic approaches to the hybrid flow shop scheduling problem with a cost-related criterion. Int J Prod Econ 105(2):407–424
Javadi B, Saidi-Mehrabad M, Haji A, Mahdavi I, Jolai F, Mahdavi-Amiri N (2008) No-wait flow shop scheduling using fuzzy multi-objective linear programming. J Franklin Inst 345:452–467
Jungwattanakit J, Reodecha M, Chaovalitwongse P, Werner F (2006) Algorithms for flexible flow shop problems with unrelated parallel machines, setup times, and dual criteria. Int J Adv Manuf Technol 37(3–4):354–370
Rahimi-Vahed AR, Javadi B, Rabbani M, Tavakkoli-Moghaddam R (2008) A multi-objective scatter search for a bi-criteria no-wait flow shop scheduling problem. Eng Optim 40(4):331–346
Rahimi-Vahed A, Dangchi M, Rafiei H, Salimi E (2009) A novel hybrid multi-objective shuffled frog-leaping algorithm for a bi-criteria permutation flow shop scheduling problem. Int J Adv Manuf Technol 41:1227–1239
Behnamian J, Fatemi Ghomi SMT (2010) Hybrid flowshop scheduling with machine and resource-dependent processing times. Appl Math Modell 35:1107–1123
Naderi B, Tavakkoli-Moghaddam R, Khalili M (2010) Electromagnetism-like mechanism and simulated annealing algorithms for flowshop scheduling problems minimizing the total weighted tardiness and makespan. Knowl Based Syst 23:77–85
Coello Coello CA (2000) Handling preferences in evolutionary multiobjective optimization: a survey. 2000 Congress on Evolutionary Computation 1. IEEE Service Center, Piscataway, New Jersey, pp 30–37
Cvetković D, Parmee IC (2002) Preferences and their application in evolutionary multiobjective optimization. IEEE Trans Evol Comput 6(1):42–57
Junker U (2004) Preference-based search and multi-criteria. Ann Oper Res 130:75–115
Ishibuchi H, Nojima Y, Narukawa K, Doi T (2006) Incorporation of decision maker’s preference into evolutionary multiobjective optimization algorithms. Proceedings of Genetic and Evolutionary Computation Conference—GECCO, New York, pp 741–742
Zitzler E, Thiele L, Bader J (2006) SPAM: set preference algorithm for multiobjective optimization. Proceedings of Conference on Parallel Problem Solving from Nature (PPSN X), Springer, pp 847–858
Luque M, Miettinen K, Eskelinen P, Ruiz F (2009) Incorporating preference information in interactive reference point methods for multiobjective optimization. Omega-Int J Manage S 37:450–462
Thiele L, Miettinen K, Korhonen PJ, Molina J (2009) A preference-based evolutionary algorithm for multiobjective optimization. Evol Comput 17(3):411–436
Wang Y, Yang Y (2009) Particle swarm optimization with preference order ranking for multi-objective optimization. Inf Sci 179:1944–1959
Cheng TCE, Wang G (2000) An improved heuristic for two-machine owshop scheduling with an availability constraint. Oper Res Lett 26:223–229
Allaoui H, Artiba A (2006) Scheduling two-stage hybrid flow shop with availability constraints. Comput Oper Res 33:1399–1419
Breit J (2006) A polynomial-time approximation scheme for the two-machine flow shop scheduling problem with an availability constraint. Comput Oper Res 33:2143–2153
Voβ S, Witt A (2007) Hybrid flow shop scheduling as a multi-mode multi-project scheduling problem with batching requirements: a real-world application. Int J Prod Econ 105:445–458
Wang X, Cheng TCE (2007) Heuristics for two-machine flowshop scheduling with setup times and an availability constraint. Comput Oper Res 34:152–162
Ruiz R, Sivrikaya-Serifoğlu F, Urlings T (2006) Modeling realistic hybrid flexible flowshop scheduling problems. Comput Oper Res 35:1151–1175
Low C, Hsu CJ, Su CT (2006) A two-stage hybrid flowshop scheduling problem with a function constraint and unrelated alternative machines. Comput Oper Res 35:845–853
Luo H, Huang GQ, Zhang YF, Dai QY, Chen X (2009) Two-stage hybrid batching flowshop scheduling with blocking and machine availability constraints using genetic algorithm. Rob Com-Int Manuf 25:962–971
Allaoui H, Artiba A (2004) Integrating simulation and optimization to schedule a hybrid flow shop with maintenance constraints. Comput Ind Eng 47:431–450
Reklaitis GV, Ravindran A, Ragsdell KM (1983) Engineering optimization methods and applications. Wiley, New York
Deb K (1995) Optimization for engineering design: algorithms and examples. Prentice-Hall, New Delhi
Davoudpour H, Ashrafi M (2009) Solving multi-objective SDST flexible flow shop using GRASP algorithm. Int J Adv Manuf Technol 44:737–747
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Sun, Y., Zhang, C., Gao, L. et al. Multi-objective optimization algorithms for flow shop scheduling problem: a review and prospects. Int J Adv Manuf Technol 55, 723–739 (2011). https://doi.org/10.1007/s00170-010-3094-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00170-010-3094-4