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A new hybrid improvement heuristic approach to simple straight and U-type assembly line balancing problems

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Abstract

This paper presents a new hybrid improvement heuristic approach to simple straight and U-type assembly line balancing problems which is based on the idea of adaptive learning approach and simulated annealing. The proposed approach uses a weight parameter to perturb task priorities of a solution to obtain improved solutions. The weight parameters are then modified using a learning strategy. The maximization of line efficiency (i.e., the minimization of the number of stations) and the equalization of workloads among stations (i.e., the minimization of the smoothness index or the minimization of the variation of workloads) are considered as the performance criteria. In order to clarify the proposed solution methodology, a well known problem taken from literature is solved. A computational study is conducted by solving a large number of benchmark problems available in the literature to compare the performance of the proposed approach to the existing methods such as simulated annealing and genetic algorithms. Some test instances taken from literature are also solved by the proposed approach. The results of the computational study show that the proposed approach performs quite effectively. It also yields optimal solutions for all test problems within a short computational time.

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References

  • Aase G.R., Schniederjans M.J. and Olson J.R. (2003). U-OPT: An analysis of exact U-shaped line balancing procedures. International Journal of Production Research 41: 4185–4210

    Article  Google Scholar 

  • Agarwal A., Colak S. and Eryarsoy E. (2006). Improvement heuristic for the flow-shop scheduling problem: An adaptive-learning approach. European Journal of Operational Research 169: 801–815

    Article  Google Scholar 

  • Aigbedo H. and Monden Y. (1997). A parametric procedure for multi-criterion sequence scheduling for just-in-time mixed-model assembly lines. International Journal of Production Research 35: 2543–2564

    Article  Google Scholar 

  • Ajenblit, D. A., & Wainwright, R. L. (1998). Applying genetic algorithms to the U-shaped assembly line balancing problem. In Proceedings of the 1998 IEEE International Conference on Evolutionary Computation, Anchorage, Alaska, pp. 96–101.

  • Bartholdi J.J. (1993). Balancing two-sided assembly lines: A case study. International Journal of Production Research 31: 2447–2461

    Article  Google Scholar 

  • Bautista J. and Pereira J. (2007). Ant algorithms for a time and space constrained assembly line balancing problem. European Journal of Operational Research 177: 2016–2032

    Article  Google Scholar 

  • Baybars I. (1986a). An efficient heuristic method for the simple assembly line balancing problem. International Journal of Production Research 24: 149–166

    Article  Google Scholar 

  • Baybars I. (1986b). A survey of exact algorithms for the simple line balancing problem. Management Science 32: 909–932

    Article  Google Scholar 

  • Baykasoğlu A. (2006). Multi-rule multi-objective simulated annealing algorithm for straight and U type assembly line balancing problems. Journal of Intelligent Manufacturing 17: 217–232

    Article  Google Scholar 

  • Becker C. and Scholl A. (2006). A survey on problems and methods in generalized assembly line balancing. European Journal of Operational Research 168: 694–715

    Article  Google Scholar 

  • Bowman E.H. (1960). Assembly line balancing by linear programming. Operations Research 8: 385–389

    Article  Google Scholar 

  • Boysen N., Fliedner M. and Scholl A. (2007). A classification of assembly line balancing problems. European Journal of Operational Research 183: 674–693

    Article  Google Scholar 

  • Chan F.T.S., Wong T.C. and Chan L.Y. (2006). Flexible job-shop scheduling problem under resource constraints. International Journal of Production Research 44(11): 2071–2089

    Article  Google Scholar 

  • Chan F.T.S., Wong T.C. and Chan L.Y. (2007). Lot streaming for product assembly in job shop environment. Robotics and Computer-Integrated Manufacturing, doi:10.1016/j.rcim.2007.01.001.

    Google Scholar 

  • Chiang W.C. (1998). The application of a tabu search metaheuristic to the assembly line balancing problem. Annals of Operations Research 77: 209–227

    Article  Google Scholar 

  • Dar-El E.M. (1973). MALB – a heuristic technique for balancing large scale single-model assembly lines. AIIE Transactions 5: 343–356

    Google Scholar 

  • Dar-El E.M. and Rubinovitch Y. (1979). MUST—a multiple solutions technique for balancing single model assembly lines. Management Science 25: 1105–1114

    Article  Google Scholar 

  • Erel E., Sabuncuoglu I. and Aksu B.A. (2001). Balancing of U-type assembly systems using simulated annealing. International Journal of Production Research 39: 3003–3015

    Article  Google Scholar 

  • Erel E. and Sarin S.C. (1998). A survey of the assembly line balancing procedures. Production Planning and Control 9: 414–434

    Article  Google Scholar 

  • Ghosh S. and Gagnon R.J. (1989). A comprehensive literature review and analysis of the design, balancing and scheduling of assembly systems. International Journal of Production Research 27: 637–670

    Article  Google Scholar 

  • Goncalves J.F. and Almeida J.R. (2002). A hybrid genetic algorithm for assembly line balancing. Journal of Heuristics 8: 629–642

    Article  Google Scholar 

  • Gökcen H. and Ağpak K. (2006). A goal programming approach to simple U-line balancing problem. European Journal of Operational Research 171: 577–585

    Article  Google Scholar 

  • Gökcen H., Ağpak K., Gencer C. and Kizilkaya E. (2005). A shortest route formulation of simple U-type assembly line balancing problem. Applied Mathematical Modelling 29: 373–380

    Article  Google Scholar 

  • Gökçen H., Ağpak K. and Benzer R. (2006). Balancing of parallel assembly lines. International Journal of Production Economics 103: 600–609

    Article  Google Scholar 

  • Heinrici, A. (1994). A comparison between simulated annealing and tabu search with an example from the production planning. In H. Dyckhoff, et al. (Eds.), Operations research proceedings 1994 (pp. 498–503). Berlin: Springer.

  • Held M., Karp R.M. and Shareshian R. (1963). Assembly line balancing—dynamic programming with precedence constraints. Operations Research 11: 442–459

    Article  Google Scholar 

  • Helgeson, W. B., Salveson, M. E., & Smith, W. W. (1954). How to balance an assembly line. Technical Report, Carr Press, New Caraan, Conn.

  • Hoffmann T.R. (1992). EUREKA: A hybrid system for assembly line balancing. Management Science 38: 39–47

    Article  Google Scholar 

  • Hwang R.K., Katayama H. and Gen M. (2007). U-shaped assembly line balancing problem with genetic algorithm. International Journal of Production Research, doi:10.1080/00207540701247906.

    Google Scholar 

  • Jackson J.R. (1956). A computing procedure for a line balancing with a precedence matrix. Management Science 2: 261–272

    Article  Google Scholar 

  • Johnson R.V. (1981). Assembly line balancing algorithms: Computational comparisons. International Journal of Production Research 19: 277–287

    Article  Google Scholar 

  • Kim Y.J., Kim Y.K. and Cho Y. (1998). A heuristic-based genetic algorithm for workload smoothing in assembly lines. Computers and Operations Research 25(2): 99–111

    Article  Google Scholar 

  • Kirkpatrick S., Gelatt C.D. and Veechi M.P. (1983). Optimization by simulated annealing. Science 220: 671–679

    Article  Google Scholar 

  • Klein M. (1963). On assembly line balancing. Operations Research 11: 274–281

    Article  Google Scholar 

  • Lapierre S.D., Ruiz A. and Soriano P. (2006). Balancing assembly lines with tabu search. European Journal of Operational Research 168: 826–837

    Article  Google Scholar 

  • Liu S.B., Ng K.M. and Ong H.L. (2008). Branch-and-bound algorithms for simple assembly line balancing problem. International Journal Advanced Manufacturing Technology 36: 169–177

    Article  Google Scholar 

  • McMullen P.R. and Frazier G.V. (1998). Using simulated annealing to solve a multi objective assembly line balancing problem with parallel workstations. International Journal of Production Research 36: 2717–2741

    Article  Google Scholar 

  • McMullen P.R. and Tarasewich P. (2003). Using ant techniques to solve the assembly line balancing problem. IIE Transactions 35: 605–617

    Article  Google Scholar 

  • Miltenburg J. (1998). Balancing U-lines in a multiple U-line facility. European Journal of Operational Research 109: 1–23

    Article  Google Scholar 

  • Miltenburg J. and Wijngaard J. (1994). The U-line line balancing problem. Management Science 40: 1378–1388

    Article  Google Scholar 

  • Moodie C.L. and Young H.H. (1965). A heuristic method of assembly line balancing for assumptions of constant or variable work element times. Journal of Industrial Engineering 16: 23–29

    Google Scholar 

  • Nearchou A.C. (2007). Multi-objective balancing of assembly lines by population heuristics. International Journal of Production Research, doi:10.1080/00207540600988089.

    Google Scholar 

  • Nevins A.J. (1972). Assembly line balancing using best bud search. Management Science 18: 529–539

    Article  Google Scholar 

  • Patterson J.H. and Albracht J.J. (1975). Assembly-line balancing: Zero-one programming with fibonacci search. Operations Research 23: 166–172

    Article  Google Scholar 

  • Ponnambalam S.G., Aravindan P. and Naidu G.M. (2000). A multi-objective genetic algorithm for solving assembly line balancing problem. International Journal of Advanced Manufacturing Technology 16: 341–352

    Article  Google Scholar 

  • Sabuncuoğlu I., Erel E. and Tanyer M. (2000). Assembly line balancing using genetic algorithms. Journal of intelligent Manufacturing 11: 295–310

    Article  Google Scholar 

  • Salveson M.E. (1955). The assembly line balancing problem. Journal of Industrial Engineering 6: 18–25

    Google Scholar 

  • Scholl, A. (1993). Data of the assembly line balancing problems. Working Paper, TH Darmstadt.

  • Scholl A. and Becker C. (2006). State-of-the-art exact and heuristic solution procedures for simple assembly line balancing. European Journal of Operational Research 168: 666–693

    Article  Google Scholar 

  • Scholl A. and Klein R. (1997). SALOME: A bidirectional branch and bound procedure for assembly line balancing. INFORMS Journal on Computing 9: 319–334

    Article  Google Scholar 

  • Scholl A. and Klein R. (1999). ULINO: Optimally balancing U-shaped JIT assembly lines. International Journal of Production Research 37(4): 721–736

    Article  Google Scholar 

  • Scholl A. and Voß S. (1996). Simple assembly line balancing—heuristic approaches. Journal of Heuristics 2: 217–244

    Article  Google Scholar 

  • Schrage L. and Baker K.R. (1978). Dynamic programming solution of sequencing problems with precedence constraints. Operations Research 26: 444–449

    Article  Google Scholar 

  • Suresh G. and Sahu S. (1994). Stochastic assembly line balancing using simulated annealing. International Journal of Production Research 32: 1801–1810

    Article  Google Scholar 

  • Tabucanon, M. T. (1988). Multiple criteria decision making in industry (Studies in production and engineering economics; 8) (pp 39–44). Amsterdam: Elsevier.

  • Talbot F.B. and Patterson J.H. (1984). An integer programming algorithm with network cuts for solving the assembly line balancing problem. Management Science 30: 85–99

    Article  Google Scholar 

  • Talbot F.B., Patterson J.H. and Gehrlein W.V. (1986). A comperative evaluation of heuristic line balancing techniques. Management Science 32: 430–454

    Article  Google Scholar 

  • Thomopoulos N.T. (1970). Mixed model line balancing with smoothed station assignments. Management Science 16: 593–603

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Tonge F.M. (1965). Assembly line balancing using probabilistic combinations of heuristics. Management Science 11: 727–735

    Article  Google Scholar 

  • Urban T.L. (1998). Optimal balancing of U-shaped assembly lines. Management Science 44: 738–741

    Article  Google Scholar 

  • Wee, T. S., & Magazine, M. (1981). An efficient branch and bound algorithm for an assembly line balancing problem – part I: Minimize the number of work stations. University of Waterloo, Ontario, Canada.

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Authors and Affiliations

  1. Department of Industrial Engineering, Selçuk University, 42075, Selçuklu, Konya, Turkey

    Uğur Özcan

  2. Department of Industrial Engineering, Gazi University, 06570, Maltepe, Ankara, Turkey

    Bilal Toklu

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  1. Uğur Özcan
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  2. Bilal Toklu
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Correspondence to Uğur Özcan.

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Özcan, U., Toklu, B. A new hybrid improvement heuristic approach to simple straight and U-type assembly line balancing problems. J Intell Manuf 20, 123–136 (2009). https://doi.org/10.1007/s10845-008-0108-2

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