Advertisement

Mathematical models and migrating birds optimization for robotic U-shaped assembly line balancing problem

  • Zixiang Li
  • Mukund Nilakantan JanardhananEmail author
  • Amira S. Ashour
  • Nilanjan Dey
Original Article
  • 73 Downloads

Abstract

Modern assembly line systems utilize robotics to replace human resources to achieve higher level of automation and flexibility. This work studies the task assignment and robot allocation in a robotic U-shaped assembly line. Two new mixed-integer programming linear models are developed to minimize the cycle time when the number of workstations is fixed. Recently developed migrating birds optimization algorithm is employed and improved to solve large-sized problems. Problem-specific improvements are also developed to enhance the proposed algorithm including modified consecutive assignment procedure for robot allocation, iterative mechanism for cycle time update, new population update mechanism and diversity controlling mechanism. An extensive comparative study is carried out to test the performance of the proposed algorithm, where seven high-performing algorithms recently reported in the literature are re-implemented to tackle the considered problem. The computational results demonstrate that the developed models are capable to achieve the optimal solutions for small-sized problems, and the proposed algorithm with these proposed improvements achieves excellent performance and outperforms the compared ones.

Keywords

Robotic U-shaped assembly line Integer programming Migrating birds optimization Artificial intelligence 

Notes

Acknowledgements

The first author acknowledges the financial support from the National Natural Science Foundation of China under Grant 61803287 and China Postdoctoral Science Foundation under grant 2018M642928.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

References

  1. 1.
    Aghajani M, Ghodsi R, Javadi B (2014) Balancing of robotic mixed-model two-sided assembly line with robot setup times. Int J Adv Manuf Technol 74:1005–1016CrossRefGoogle Scholar
  2. 2.
    Akpınar S, Mirac Bayhan G (2011) A hybrid genetic algorithm for mixed model assembly line balancing problem with parallel workstations and zoning constraints. Eng Appl Artif Intell 24:449–457CrossRefGoogle Scholar
  3. 3.
    Avikal S, Jain R, Mishra PK, Yadav HC (2013) A heuristic approach for U-shaped assembly line balancing to improve labor productivity. Comput Ind Eng 64:895–901CrossRefGoogle Scholar
  4. 4.
    Bagher M, Zandieh M, Farsijani H (2011) Balancing of stochastic U-type assembly lines: an imperialist competitive algorithm. Int J Adv Manuf Tech 54:271–285CrossRefGoogle Scholar
  5. 5.
    Baykasoglu A, Dereli T (2009) Simple and U-type assembly line balancing by using an ant colony based algorithm. Math Comput Appl 14:1–12zbMATHGoogle Scholar
  6. 6.
    Chiang W-C, Urban TL (2006) The stochastic U-line balancing problem: a heuristic procedure. Eur J Oper Res 175:1767–1781CrossRefGoogle Scholar
  7. 7.
    Çil ZA, Mete S, Ağpak K (2017) Analysis of the type II robotic mixed-model assembly line balancing problem. Eng Optim 49:990–1009MathSciNetCrossRefGoogle Scholar
  8. 8.
    Çil ZA, Mete S, Özceylan E, Ağpak K (2017) A beam search approach for solving type II robotic parallel assembly line balancing problem. Appl Soft Comput 61:129–138CrossRefGoogle Scholar
  9. 9.
    Daoud S, Chehade H, Yalaoui F, Amodeo L (2014) Solving a robotic assembly line balancing problem using efficient hybrid methods. J Heuristics 20:235–259CrossRefGoogle Scholar
  10. 10.
    Duman E, Uysal M, Alkaya AF (2012) Migrating birds optimization: a new metaheuristic approach and its performance on quadratic assignment problem. Inf Sci 217:65–77MathSciNetCrossRefGoogle Scholar
  11. 11.
    Erel E, Sabuncuoglu I, Aksu BA (2001) Balancing of U-type assembly systems using simulated annealing. Int J Prod Res 39:3003–3015CrossRefGoogle Scholar
  12. 12.
    Fattahi A, Turkay M (2015) On the MILP model for the U-shaped assembly line balancing problems. Eur J Oper Res 242:343–346MathSciNetCrossRefGoogle Scholar
  13. 13.
    Gao J, Sun L, Wang L, Gen M (2009) An efficient approach for type II robotic assembly line balancing problems. Comput Ind Eng 56:1065–1080CrossRefGoogle Scholar
  14. 14.
    Gao L, Pan Q-K (2016) A shuffled multi-swarm micro-migrating birds optimizer for a multi-resource-constrained flexible job shop scheduling problem. Inf Sci 372:655–676CrossRefGoogle Scholar
  15. 15.
    Gokcen H, Agpak K (2006) A goal programming approach to simple U-line balancing problem. Eur J Oper Res 171:577–585MathSciNetCrossRefGoogle Scholar
  16. 16.
    Hamta N, Fatemi Ghomi SMT, 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 141:99–111CrossRefGoogle Scholar
  17. 17.
    Hwang RK, Katayama H, Gen M (2008) U-shaped assembly line balancing problem with genetic algorithm. Int J Prod Res 46:4637–4649CrossRefGoogle Scholar
  18. 18.
    Khorasanian D, Hejazi SR, Moslehi G (2013) Two-sided assembly line balancing considering the relationships between tasks. Comput Ind Eng 66:1096–1105CrossRefGoogle Scholar
  19. 19.
    Kim YK, Kim JY, Kim Y (2006) An endosymbiotic evolutionary algorithm for the integration of balancing and sequencing in mixed-model U-lines. Eur J Oper Res 168:838–852MathSciNetCrossRefGoogle Scholar
  20. 20.
    Kim YK, Kim SJ, Kim JY (2000) Balancing and sequencing mixed-model U-lines with a co-evolutionary algorithm. Prod Plan Control 11:754–764CrossRefGoogle Scholar
  21. 21.
    Kucukkoc I, Zhang DZ (2015) Balancing of parallel U-shaped assembly lines. Comput Oper Res 64:233–244MathSciNetCrossRefGoogle Scholar
  22. 22.
    Levitin G, Rubinovitz J, Shnits B (2006) A genetic algorithm for robotic assembly line balancing. Eur J Oper Res 168:811–825MathSciNetCrossRefGoogle Scholar
  23. 23.
    Li Z, Dey N, Ashour AS, Tang Q (2017a) Discrete cuckoo search algorithms for two-sided robotic assembly line balancing problem. Neural Comput Appl 30:2685–2696CrossRefGoogle Scholar
  24. 24.
    Li Z, Janardhanan MN, Tang Q, Nielsen P (2017) Mathematical model and metaheuristics for simultaneous balancing and sequencing of a robotic mixed-model assembly line. Eng Optim 50:877–893MathSciNetCrossRefGoogle Scholar
  25. 25.
    Li Z, Kucukkoc I, Nilakantan JM (2017) Comprehensive review and evaluation of heuristics and meta-heuristics for two-sided assembly line balancing problem. Comput Oper Res 84:146–161MathSciNetCrossRefGoogle Scholar
  26. 26.
    Li Z, Kucukkoc I, Tang Q (2017d) New MILP model and station-oriented ant colony optimization algorithm for balancing U-type assembly lines. Comput Ind Eng 112:107–121CrossRefGoogle Scholar
  27. 27.
    Li Z, Nilakantan JM, Tang Q, Nielsen P (2016) Co-evolutionary particle swarm optimization algorithm for two-sided robotic assembly line balancing problem. Adv Mech Eng 8:1–14Google Scholar
  28. 28.
    Li Z, Tang Q, Zhang L (2016) Minimizing energy consumption and cycle time in two-sided robotic assembly line systems using restarted simulated annealing algorithm. J Cleaner Prod 135:508–522CrossRefGoogle Scholar
  29. 29.
    Miltenburg GJ, Wijngaard J (1994) The U-line line balancing problem. Manag Sci 40:1378–1388CrossRefGoogle Scholar
  30. 30.
    Miltenburg J (1998) Balancing U-lines in a multiple U-line facility. Eur J Oper Res 109:1–23CrossRefGoogle Scholar
  31. 31.
    Nakade K, Ohno K (1999) An optimal worker allocation problem for a U-shaped production line. Int J Prod Econ 60–61:353–358CrossRefGoogle Scholar
  32. 32.
    Nilakantan JM, Huang GQ, Ponnambalam S (2015) An investigation on minimizing cycle time and total energy consumption in robotic assembly line systems. J Clean Prod 90:311–325CrossRefGoogle Scholar
  33. 33.
    Nilakantan JM, Ponnambalam S (2016) Robotic U-shaped assembly line balancing using particle swarm optimization. Eng Optim 48:231–252MathSciNetCrossRefGoogle Scholar
  34. 34.
    Nilakantan JM, Ponnambalam SG, Jawahar N, Kanagaraj G (2015) Bio-inspired search algorithms to solve robotic assembly line balancing problems. Neural Comput Appl 26:1379–1393CrossRefGoogle Scholar
  35. 35.
    Ogan D, Azizoglu M (2015) A branch and bound method for the line balancing problem in U-shaped assembly lines with equipment requirements. J Manuf Syst 36:46–54CrossRefGoogle Scholar
  36. 36.
    Rabbani M, Kazemi SM, Manavizadeh N (2012) Mixed model U-line balancing type-1 problem: a new approach. J Manuf Syst 31:131–138CrossRefGoogle Scholar
  37. 37.
    Rubinovitz J, Bukchin J (1991) Design and balancing of robotic assembly lines. In: Proceedings of the fourth world conference on robotics research. Pittsburgh, PAGoogle Scholar
  38. 38.
    Rubinovitz J, Bukchin J, Lenz E (1993) RALB—a heuristic algorithm for design and balancing of robotic assembly lines. CIRP Ann Manuf Technol 42:497–500CrossRefGoogle Scholar
  39. 39.
    Sabuncuoglu I, Erel E, Alp A (2009) Ant colony optimization for the single model U-type assembly line balancing problem. Int J Prod Econ 120:287–300CrossRefGoogle Scholar
  40. 40.
    Saif U, Guan Z, Liu W, Wang B, Zhang C (2014) Multi-objective artificial bee colony algorithm for simultaneous sequencing and balancing of mixed model assembly line. Int J Adv Manuf Technol 75:1809–1827CrossRefGoogle Scholar
  41. 41.
    Scholl A, Klein R (1999) ULINO: optimally balancing U-shaped JIT assembly lines. Int J Prod Res 37:721–736CrossRefGoogle Scholar
  42. 42.
    Tang QH, Li ZX, Zhang LP, Floudas CA, Cao XJ (2015) Effective hybrid teaching-learning-based optimization algorithm for balancing two-sided assembly lines with multiple constraints. Chin J Mech Eng 28:1067–1079CrossRefGoogle Scholar
  43. 43.
    Ulker E, Tongur V (2017) Migrating birds optimization (MBO) algorithm to solve knapsack problem. Proc Comput Sci 111:71–76CrossRefGoogle Scholar
  44. 44.
    Urban TL (1998) Note. optimal balancing of U-shaped assembly lines. Manag Sci 44:738–741CrossRefGoogle Scholar
  45. 45.
    Urban TL, Chiang W-C (2006) An optimal piecewise-linear program for the U-line balancing problem with stochastic task times. Eur J Oper Res 168:771–782MathSciNetCrossRefGoogle Scholar
  46. 46.
    Yoosefelahi A, Aminnayeri M, Mosadegh H, Ardakani HD (2012) Type II robotic assembly line balancing problem: an evolution strategies algorithm for a multi-objective model. J Manuf Syst 31:139–151CrossRefGoogle Scholar
  47. 47.
    Zacharia PT, Nearchou AC (2016) A population-based algorithm for the bi-objective assembly line worker assignment and balancing problem. Eng Appl Artif Intell 49:1–9CrossRefGoogle Scholar
  48. 48.
    Zhang B, Pan Q-K, Gao L, Zhang X-L, Sang H-Y, Li J-Q (2017) An effective modified migrating birds optimization for hybrid flowshop scheduling problem with lot streaming. Appl Soft Comput 52:14–27CrossRefGoogle Scholar

Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2019

Authors and Affiliations

  1. 1.Key Laboratory of Metallurgical Equipment and Control TechnologyWuhan University of Science and TechnologyWuhanChina
  2. 2.Hubei Key Laboratory of Mechanical Transmission and Manufacturing EngineeringWuhan University of Science and TechnologyWuhanChina
  3. 3.Mechanics of Materials Research Group, Department of EngineeringUniversity of LeicesterLeicesterUK
  4. 4.Department of Electronics and Electrical Communication Engineering, Faculty of EngineeringTanta UniversityTantaEgypt
  5. 5.Department of Information TechnologyTechno India College of TechnologyKolkataIndia

Personalised recommendations