Mixed-Model Assembly Line Sequencing Using Real Options

Alireza Rahimi-Vahed (), Masoud Rabbani, Reza Tavakkoli-Moghaddam, Fariborz Jolai and Neda Manavizadeh
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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

A chapter in Operations Research Proceedings 2006, 2007, pp 161-167 from Springer

Abstract: 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.

Keywords: Tabu Search; Real Option; Memetic Algorithm; Part Usage; Real Option Model (search for similar items in EconPapers)
Date: 2007
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DOI: 10.1007/978-3-540-69995-8_27

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