Skip to main content

Multi-objective Approaches for Design of Assembly Lines

  • Chapter
  • First Online:
Applications of Multi-Criteria and Game Theory Approaches

Part of the book series: Springer Series in Advanced Manufacturing ((SSAM))

Abstract

This chapter deals with the use of multi-objective approaches in the field of assembly line design. The design of assembly or transfer lines is a very important industrial problem, which involves various difficult and interconnected optimization problems. A review of the main multi-objective optimization methods used for these problems is presented and discussed. A case study is also described in order to highlight some interesting properties associated with such multi-objective problems.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Baykasoğlu A (2006) Multi-rule multi-objective simulated annealing algorithm for straight and U type assembly line balancing problems. J Intell Manuf 17(2):217–232

    Article  Google Scholar 

  • Bigras L, Gamache M, Savard G (2008) The time-dependent traveling salesman problem and single machine scheduling problems with sequence dependent setup times. Dis Opt 5(4):685–699

    Article  MathSciNet  MATH  Google Scholar 

  • Borisovsky P, Delorme X, Dolgui A (2012) Genetic algorithm for balancing reconfigurable machining lines. Comput Ind Eng. doi:10.1016/j.cie.2012.12.009

  • Bukchin J, Masin M (2004) Multi-objective design of team oriented assembly systems. Eur J Oper Res 156(2):326–352

    Article  MATH  Google Scholar 

  • Cakir B, Altiparmak F, Dengiz B (2011) Multi-objective optimization of a stochastic assembly line balancing: a hybrid simulated annealing algorithm. Comput Ind Eng 60(3):376–384

    Article  Google Scholar 

  • Chen JH, Ho SY (2005) A novel approach to production planning of flexible manufacturing systems using an efficient multi-objective genetic algorithm. Int J Mach Tools Manuf 45(7–8):949–957

    Article  Google Scholar 

  • Cheshmehgaz H, Haron H, Kazemipour F, Desa M (2012) Accumulated risk of body postures in assembly line balancing problem and modeling through a multi-criteria fuzzy-genetic algorithm. Comput Ind Eng 63(2):503–512

    Article  Google Scholar 

  • Chica M, Cordón O, Damas S (2011a) An advanced multi-objective genetic algorithm design for the time and space assembly line balancing problem. Comput Ind Eng 61(1):103–117

    Article  Google Scholar 

  • Chica M, Cordón O, Damas S, Bautista J (2011b) Including different kinds of preferences in a multi-objective ant algorithm for time and space assembly line balancing on different Nissan scenarios. Exp Syst Appl 38(1):709–720

    Article  Google Scholar 

  • Chica M, Cordón O, Damas S, Bautista J (2012) Multi-objective memetic algorithms for time and space assembly line balancing. Eng Appl Artif Intell 25(2):254–273

    Article  Google Scholar 

  • Chica M, Cordón O, Damas S, Bautista J, Pereira J (2010) Multi-objective constructive heuristics for the 1/3 variant of the time and space assembly line balancing problem: ACO and random greedy search. Inf Sci 180(18):3465–3487

    Article  Google Scholar 

  • Chutima P, Chimklai P (2012) Multi-objective two-sided mixed-model assembly line balancing using particle swarm optimisation with negative knowledge. Comput Ind Eng 62(1):39–55

    Article  Google Scholar 

  • Chutima P, Olanviwatchai P (2010) Mixed-model U-shaped assembly line balancing problems with coincidence memetic algorithm. J Softw Eng Appl 3(4):347–363

    Article  Google Scholar 

  • Deckro R, Rangachari S (1990) A goal approach to assembly line balancing. Comput Oper Res 17(5):509–521

    Article  MATH  Google Scholar 

  • Delorme X, Dolgui A, Essafi M, Linxe L, Poyard D (2009) Machining lines automation. In: Nof DS (ed) Handbook of automation. Springer, New York, pp 599–617

    Google Scholar 

  • Ding LP, Feng YX, Tan JR, Gao YC (2010) A new multi-objective ant colony algorithm for solving the disassembly line balancing problem. Int J Adv Manuf Technol 48(5–8):761–771

    Article  Google Scholar 

  • Duta L, Filip F, Henrioud JM (2003) A method for dealing with multi-objective optimization problem of disassembly processes. In: Proceedings of the 5th IEEE intemational symposium on assembly and task planning, Besançon, pp 163–168

    Google Scholar 

  • Essafi M, Delorme X, Dolgui A (2012) A reactive GRASP and path relinking for balancing reconfigurable transfer lines. Int J Prod Res 50(18):5213–5238

    Article  Google Scholar 

  • Essafi M, Delorme X, Dolgui A, Guschinskaya O (2010) A MIP approach for balancing transfer line with complex industrial constraints. Comput Ind Eng 58(3):393–400

    Article  Google Scholar 

  • Fattahi P, Roshani A, Roshani A (2011) A mathematical model and ant colony algorithm for multi-manned assembly line balancing problem. Int J Adv Manuf Technol 53(1–4):363–378

    Article  Google Scholar 

  • Gamberini R, Grassi A, Rimini B (2006) A new multi-objective heuristic algorithm for solving the stochastic assembly line re-balancing problem. Int J Prod Econ 102(2):226–243

    Article  Google Scholar 

  • Gamberini R, Grassi E, Regattieri A (2009) A multiple single-pass heuristic algorithm solving the stochastic assembly line rebalancing problem. Int J Prod Res 47(8):2141–2164

    Article  MATH  Google Scholar 

  • Gökçen H, Ağpak K (2006) A goal programming approach to simple U-line balancing problem. Eur J Oper Res 171(2):577–585

    Article  MATH  Google Scholar 

  • Gökçen H, Erel E (1997) A goal programming approach to mixed-model assembly line balancing problem. Int J Prod Econ 48(2):177–185

    Article  Google Scholar 

  • Gupta S, McGovern S (2004) Multi-objective optimization in disassembly sequencing problems. In: Second world conference on POM and 15th annual POM conference, Cancun

    Google Scholar 

  • Hamta N, Fatemi Ghomi S, Jolai F, Akbarpour Shirazi M (2013) A hybrid PSO algorithm for a multi-objective assembly line balancing problem with flexible operation times, sequence-dependent setup times and learning effect. Int J Prod Econ 141(1):99–111

    Article  Google Scholar 

  • Hamta N, Fatemi Ghomi S, Jolai F, Bahalke U (2011) Bi-criteria assembly line balancing by considering flexible operation times. Appl Math Model 35(12):5592–5608

    Article  MathSciNet  MATH  Google Scholar 

  • Hwang R, Katayama H (2009) A multi-decision genetic approach for workload balancing of mixed-model U-shaped assembly line systems. Int J Prod Res 47(14):3797–3822

    Article  Google Scholar 

  • Hwang R, Katayama H (2010) Integrated procedure of balancing and sequencing for mixed-model assembly lines: a multi-objective evolutionary approach. Int J Prod Res 48(21):6417–6441

    Article  MATH  Google Scholar 

  • Hwang R, Katayama H, Gen M (2008) U-shaped assembly line balancing problem with genetic algorithm. Int J Prod Res 46(16):4637–4650

    Article  MATH  Google Scholar 

  • Kara Y, Ozcan U, Peker A (2007) Balancing and sequencing mixed-model just-in-time U-lines with multiple objectives. Appl Math Comp 184(2):566–588

    Article  MathSciNet  MATH  Google Scholar 

  • Kara Y, Özgüven C, Seçme N, Chang C (2011) Multi-objective approaches to balance mixed-model assembly lines for model mixes having precedence conflicts and duplicable common tasks. Int J Adv Manuf Techn 52(5–8):725–737

    Article  Google Scholar 

  • Kim Y, Kim Y, Kim Y (1996) Genetic algorithms for assembly line balancing with various objectives. Comput Ind Eng 30(3):397–409

    Article  Google Scholar 

  • Koren Y, Heisel U, Jovane F, Moriwaki T, Pritschow G, Ulsoy G et al (1999) Reconfigurable manufacturing systems. CIRP Ann Manuf Technol 48(2):527–540

    Article  Google Scholar 

  • Leu YY, Matheson L, Rees L (1994) Assembly line balancing using genetic algorithms with heuristic-generated initial populations and multiple evaluation criteria. Dec Sci 25(4):581–606

    Article  Google Scholar 

  • Malakooti B (1991) A multiple criteria decision making approach for the assembly line balancing problem. Int J Prod Res 29(10):1979–2001

    Article  MATH  Google Scholar 

  • Malakooti B, Kumar A (1996) A knowledge-based system for solving multi-objective assembly line balancing problems. Int J Prod Res 34(9):2533–2552

    Article  MATH  Google Scholar 

  • McMullen P, Frazier G (1998) Using simulated annealing to solve a multi-objective assembly line balancing problem with parallel workstations. Int J Prod Res 36(10):2717–2741

    Article  MATH  Google Scholar 

  • McMullen P, Tarasewich P (2006) Multi-objective assembly line balancing via a modified ant colony optimization technique. Int J Prod Res 44(1):27–42

    Article  MATH  Google Scholar 

  • Nearchou AC (2008) Multi-objective balancing of assembly lines by population heuristics. Int J Prod Res 46(8):2275–2298

    Article  MATH  Google Scholar 

  • Nearchou A (2011) Maximizing production rate and workload smoothing in assembly lines using particle swarm optimization. Int J Prod Econ 129(2):242–250

    Article  Google Scholar 

  • Nof S, Wilhem W, Warnecke H (1997) Industrial assembly. Chapman Hall, London

    Book  Google Scholar 

  • Nourmohammadi A, Zandieh M (2011) Assembly line balancing by a new multi-objective differential evolution algorithm based on TOPSIS. Int J Prod Res 49(10):2833–2855

    Article  Google Scholar 

  • Özcan U, Toklu B (2009a) A tabu search algorithm for two-sided assembly line balancing. Int J Adv Manuf Techn 43(7):822–829

    Article  Google Scholar 

  • Özcan U, Toklu B (2009b) Balancing of mixed-model two-sided assembly lines. Comput Ind Eng 57(1):217–227

    Article  Google Scholar 

  • Özcan U, Toklu B (2010) Balancing two-sided assembly lines with sequence-dependent setup times. Int J Prod Res 48(18):5363–5383

    Article  MATH  Google Scholar 

  • Pastor R (2011) LB-ALBP: the lexicographic bottleneck assembly line balancing problem. Int J Prod Res 49(8):2424–2442

    Article  MathSciNet  Google Scholar 

  • Pastor R, Andrés C, Duran A, Pérez M (2002) Tabu search algorithms for an industrial multi-product and multi-objective assembly line balancing problem, with reduction of the task dispersion. J Oper Res Soc 53(12):1317–1323

    Article  MATH  Google Scholar 

  • Pekin N, Azizoglu M (2008) Bi criteria flexible assembly line design problem with equipment decisions. Int J Prod Res 46(22):6323–6343

    Article  MATH  Google Scholar 

  • Ponnambalam S, Aravindan P, Mogileeswar Naidu G (2000) A multi-objective genetic algorithm for solving assembly line balancing problem. Int J Adv Manuf Technol 16:341–352

    Article  Google Scholar 

  • Purnomo H, Wee H, Rau H (2013) Two-sided assembly lines balancing with assignment restrictions. Math Comp Model 57(1–2):189–199

    Article  Google Scholar 

  • Rekiek B, De Lit P, Pellichero F, L’Eglise T, Fouda P, Falkenauer E et al (2001) A multiple objective grouping genetic algorithm for assembly line design. J Intell Manuf 12(5–6):467–485

    Article  Google Scholar 

  • Sawik T (1997) An interactive approach to bicriterion loading of a flexible assembly system. Math Comp Model 25(6):71–83

    Article  MathSciNet  MATH  Google Scholar 

  • Sawik T (1998) A lexicographic approach to bi-objective loading of a flexible assembly system. Eur J Oper Res 107(3):656–668

    Article  MATH  Google Scholar 

  • Shin K, Park JO, Kim Y (2011) Multi-objective FMS process planning with various flexibilities using a symbiotic evolutionary algorithm. Comput Oper Res 38:702–712

    Article  MathSciNet  MATH  Google Scholar 

  • Simaria A, Zanella de Sá M, Vilarinho P (2009) Meeting demand variation using flexible U-shaped assembly lines. Int J Prod Res 47(14):3937–3955

    Article  MATH  Google Scholar 

  • Suwannarongsri S, Puangdownreong D (2009) Metaheuristic approach to assembly line balancing. WSEAS transactions on systems 2(8):200–209

    Google Scholar 

  • Toklu B, Özcan U (2008) A fuzzy goal programming model for the simple U-line balancing problem with multiple objectives. Eng Optim 40(3):191–204

    Article  MathSciNet  Google Scholar 

  • Yang C, Gao J, Sun L (2013) A multi-objective genetic algorithm for mixed-model assembly rebalancing. Comput Ind Eng 65(1):109-116

    Google Scholar 

  • Yoosefelahi A, Aminnayeri M, Mosadegh H, Davari Ardakahi H (2012) Type II robotic assembly line balancing problem: an evolution strategies algorithm for a multi-objective mode. J Manuf Syst 31(2):139–151

    Article  Google Scholar 

  • Zacharia P, Nearchou A (2012) Multi-objective fuzzy assembly line balancing using genetic algorithms. J Intell Manuf 23(3):615–627

    Article  Google Scholar 

  • Zhang W, Gen M (2011) An efficient multi-objective genetic algorithm for mixed-model assembly line balancing problem considering demand ratio-based cycle time. J Intell Manuf 22(3):367–378

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to X. Delorme .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer-Verlag London

About this chapter

Cite this chapter

Delorme, X., Battaïa, O., Dolgui, A. (2014). Multi-objective Approaches for Design of Assembly Lines. In: Benyoucef, L., Hennet, JC., Tiwari, M. (eds) Applications of Multi-Criteria and Game Theory Approaches. Springer Series in Advanced Manufacturing. Springer, London. https://doi.org/10.1007/978-1-4471-5295-8_2

Download citation

  • DOI: https://doi.org/10.1007/978-1-4471-5295-8_2

  • Published:

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-5294-1

  • Online ISBN: 978-1-4471-5295-8

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics