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Mixed-Model Assembly Line Sequencing Using Real Options

In: Operations Research Proceedings 2006

Author

Listed:
  • Alireza Rahimi-Vahed

    (University of Tehran)

  • Masoud Rabbani

    (University of Tehran)

  • Reza Tavakkoli-Moghaddam

    (University of Tehran)

  • Fariborz Jolai

    (University of Tehran)

  • Neda Manavizadeh

    (University of Tehran)

Abstract

Monden [11] defined two goals for the mixed-model assembly line sequencing problem: (1) Leveling the load on each station on the line, and (2) Keeping a constant rate of usage of every part used by the line. To handle these problems, Goal chasing I and II (GC- I and GC- II ) were developed by Toyota corporation. Miltenburg [9]developed a nonlinear programming for the second goal and solved the problem by applying tow heuristic procedures. Miltenberg et al [10] solved the same problem with a dynamic programming algorithm. The objective considered by Bard et al [1] was the minimization of overall line length. Bard et al [2] used Tabu search (TS) algorithm to solve a model involving two objectives: minimizing the overall line length and keeping a constant rate of part usage. Hyun et al [4] addressed three objectives: minimizing total utility work, keeping a constant rate of part usage and minimizing total setup cost. This problem was solved by proposing a new genetic evaluation. Mcmullen [6] considered two objectives: minimizing number of setups and keeping a constant rate of part usage. He solved this problem with a TS approach. Mcmullen [7,8] has also solved the same problem by using genetic algorithm, and ant colony optimization, respectively.

Suggested Citation

  • Alireza Rahimi-Vahed & Masoud Rabbani & Reza Tavakkoli-Moghaddam & Fariborz Jolai & Neda Manavizadeh, 2007. "Mixed-Model Assembly Line Sequencing Using Real Options," Operations Research Proceedings, in: Karl-Heinz Waldmann & Ulrike M. Stocker (ed.), Operations Research Proceedings 2006, pages 161-167, Springer.
    • Handle: RePEc:spr:oprchp:978-3-540-69995-8_27
    DOI: 10.1007/978-3-540-69995-8_27
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