Bicriteria sequencing methods for the mixed-model assembly line in just-in-time production systems

Korkmazel, Tuğrul; Meral, Sedef

doi:10.1016/s0377-2217(00)00061-8

Cited by 61 publications

(19 citation statements)

References 21 publications

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“…Korkmazel and Meral (17) and Tavakkkoli-Moghaddam (18) . Recently, Rahimi-Vahed et al (19) developed a multi-objective scatter search algorithm for solving a multi-objective sequencing problem under three objectives, i.e., minimization of total utility work, total production rate variation, and total setup cost.…”

Section: A Brief Literature Reviewmentioning

confidence: 99%

Multi-Objective Analysis Applied to Mixed-Model Assembly Line Sequencing Problem through Elite Induced Evolutionary Method

Shimizu

Sakaguchi

Pralomkarn

2012

JAMDSM

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To meet higher customer satisfaction and shorter production lead time, assembly lines are shifting to mixed-model assembly lines. Accordingly, sequencing is becoming an increasingly important operation scheduling that directly affects on efficiency of the entire process. In this study, such sequencing problem at the mixed-model assembly line has been formulated as a bi-objective integer programming problem so that decision making through trade-off analysis can bring about significant production improvements. Then we have developed a multi-objective analysis method by hybridizing conventional and recent meta-heuristic methods. After showing its generic idea, the car mixed-model assembly line sequencing problem is concerned as a case study. Certain measures are also introduced to quantitatively evaluate the performances of the method through comparison.

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Section: A Brief Literature Reviewmentioning

confidence: 99%

Multi-Objective Analysis Applied to Mixed-Model Assembly Line Sequencing Problem through Elite Induced Evolutionary Method

Shimizu

Sakaguchi

Pralomkarn

2012

JAMDSM

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“…Such concern has been paid on the smooth operation of the lot production and the level production for the assembly line (For instances, Korkmazel and Meral (5) and Rahimi-Vahed, et al. (7) ).…”

Section: Brief Literature Reviewmentioning

confidence: 99%

Multi-Objective Sequencing Optimization for Mixed-Model Assembly Line Considering Due-Date Satisfaction

Shimizu

Waki

Sakaguchi

2012

JAMDSM

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To meet higher customer satisfaction and shorter production lead time under rapidly changing demands and global competition, importance of just-in-time and agile manufacturing is raising much more attentions than before. To cope with such circumstances, assembly line is shifting to mixed-model assembly line. Under such situation, it is essential to extend system boundary wider and resolve the problem totally. Moreover, in this study, we pay our attention to the latest production manner applied in car industry and extend our conventional model associated with due dates of finished products. Finally, we have formulated a bi-objective optimization problem that aims at reducing total sum of tardiness and total volume of inventories at the same time. Besides the usual one-through approach to solve the resulting problem, we adopt a two stage approach associated with multi-objective analysis. To reveal some properties of the proposed approaches, we provide a case study and discuss effectiveness of the method and usefulness of the results.

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“…Duplaga and Bragg (1998) address the mixed-model sequencing problem which smoothes out the rate of use of each component part by providing a controlled comparison of six sequencing heuristics. Several researchers such as Zeramdini et al (2000), Korkmazel and Meral (2001), and Kotani and Ohno (2001) propose a bicriteria sequencing for mixed-model assembly lines, where two goals are: (1) keeping a constant rate of usage of parts and (2) smoothing the workload at work stations. McMullen and Frazier (2000) present a simulated annealing based heuristic that simultaneously considers both setups and the stability of parts usage rates.…”

Section: Introductionmentioning

confidence: 99%

Sequencing the Mixed Model Assembly Line with Multiple Stations to Minimize the Total Utility Work and Idle Time

Kim

Choi²

2016

Industrial Engineering and Management Systems

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This paper presents a fast sequencing algorithm for a mixed model assembly line with multiple workstations which minimize the total utility work and idle time. We compare the proposed algorithms with another heuristic, the Tsaibased heuristic, for a sequencing problem that minimizes the total utility works. Numerical experiments are used to evaluate the performance and effectiveness of the proposed algorithm. The Tsai-based heuristic performs best in terms of utility work, but the fast sequencing algorithm performs well for both utility work and idle time. However, the computational complexity of the fast sequencing algorithm is O (KN) while the Tsai-based algorithm is O (KNlogN). Actual computational time of the fast sequencing heuristic is 2-6 times faster than that of the Tsai-based heuristic.

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Bicriteria sequencing methods for the mixed-model assembly line in just-in-time production systems

Cited by 61 publications

References 21 publications

Multi-Objective Analysis Applied to Mixed-Model Assembly Line Sequencing Problem through Elite Induced Evolutionary Method

Multi-Objective Analysis Applied to Mixed-Model Assembly Line Sequencing Problem through Elite Induced Evolutionary Method

Multi-Objective Sequencing Optimization for Mixed-Model Assembly Line Considering Due-Date Satisfaction

Sequencing the Mixed Model Assembly Line with Multiple Stations to Minimize the Total Utility Work and Idle Time

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