Mixed-model assembly line balancing in the make-to-order and stochastic environment using multi-objective evolutionary algorithms

Manavizadeh, Neda; Rabbani, Masoud; Moshtaghi, Davoud; Jolai, Fariborz

doi:10.1016/j.eswa.2012.03.044

Cited by 39 publications

(14 citation statements)

References 15 publications

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“…Otro aspecto que ha sido considerado en algunas investigaciones en líneas de modelos mixtos es la inclusión de líneas de dos lados como en [5,6]; otras investiga-ciones involucran la variabilidad en algunos de sus parámetros lo cual se puede ver en [7] y [8]; por su parte en [9 -11] emplean los enfoques multi-objetivo en las líneas de modelos mixtos; además, [12 -14] introduce el problema de tiempos de alistamiento a este tipo de líneas.…”

Section: Revisión Bibliográficaunclassified

Balance horizontal de líneas de ensamble para modelos mixtos

Cruz

Cabrera

Dorado

2015

rev.ing.univ.Medellin

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ResumenLas líneas de ensamble tradicionalmente han sido utilizadas para producir grandes cantidades de un único modelo. Para aprovechar las ventajas de estas en ambientes de manufactura flexibles, se pueden implementar líneas de modelos mixtos las cuales permiten ensamblar diferentes productos de una familia en una misma línea; sin embargo, su balanceo requiere técnicas diferentes de las tradicionales. En esta investigación se hizo una revisión bibliográfica para analizar los factores que afectan las líneas de modelos mixtos y con base en esto se desarrolló un modelo de optimización matemática que estabiliza las cargas de trabajo, facilitando la decisión sobre las secuencias de producción que se programan en la línea. El modelo se corrió en varios escenarios y se obtuvieron resultados significativamente mejores que los obtenidos con un método tradicional de balance.Palabras clave: balance de línea, modelos mixtos, balance horizontal.

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Section: Revisión Bibliográficaunclassified

Balance horizontal de líneas de ensamble para modelos mixtos

Cruz

Cabrera

Dorado

2015

rev.ing.univ.Medellin

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“…The names that correspond to each job element are listed in Table III. 1 2 3 6 4 5 19 20 21 22 23 24 25 26 7 8 9 10 11 12 13 14 15 16 17 18 29 27 28 30 31 32 33 34 35 36 The company produces a total of 12 types of chillers, of which there are three representative models whose processing time follows the distribution of N(m 1 ,  (9) According to the combination optimization method proposed in this paper, we first undertake one optimization by equating the operation time at each process with time spent by skilful workers to operate on the running machine. Meanwhile, we extract other related parameters.…”

Section: Example Applicationmentioning

confidence: 99%

“…Erel and Gokcen [6], Gökçen et al [7] proposed the shortest route algorithm tailor-made for the hybrid production assembly line, which can only be applied to the large-scale assembly line balancing problem in a limited way. Pierreval et al [8], Manavizadeh et al [9], Koç [10] used the GA to explore this issue. Meanwhile, the GA was used to improve the balancing issue [11,12].…”

Section: Introductionmentioning

confidence: 99%

Research on Industrial Assembly Line Balancing Optimization Based on Genetic Algorithm and Witness Simulation

Wang¹,

Yang²

2017

Int. j. simul. model.

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With the rapid development of the industry sector, the assembly line has also experienced development, whose rationality determines the production efficiency of industrial production. In this paper, in order to address the balancing issue of assembly lines for industrial production, a combinatorial optimization method is proposed for the optimization and implementation of the assembly line based on the improved genetic algorithm (GA) and system simulation. By being applied to the assembly line of a company's chiller, our method is proved practical and effective.

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“…Mixed-model lines enable production of different product models on the same line in an intermixed sequence (Boysen et al, 2008;Kucukkoc and Zhang, 2014). Various heuristic, meta-heuristic, and exact solution approaches have been proposed for solving the mixed-model assembly line balancing problem; e.g., Kara et al (2007), Ozcan and Toklu (2009a), Ozcan et al (2010a), Mosadegh et al (2012), and Manavizadeh et al (2013) developed simulated annealing approaches; Ozcan et al (2011), Xu andXiao (2011), Akpinar andBayhan (2011), Hamzadayi and Yildiz (2012), and Manavizadeh et al (2012) developed genetic algorithm techniques; Simaria and Vilarinho (2009) and Yagmahan (2011) developed ant colony optimization (ACO) techniques, and Akpinar et al (2013) hybridized ACO with a genetic algorithm. Simaria and Vilarinho (2009) developed a mathematical model and Yagmahan (2011) considered multiple objectives as well as minimizing the total number of workstations.…”

Section: Introductionmentioning

confidence: 99%

Mixed-model parallel two-sided assembly line balancing problem: A flexible agent-based ant colony optimization approach

Küçükkoç

Zhang

2016

Computers & Industrial Engineering

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Assembly lines are frequently used as a production method to assemble complex products. Two-sided assembly lines are utilized to assemble large-sized products (e.g., cars, buses, trucks). Locating two lines in parallel helps improve line efficiency by enabling collaboration between the line workers. This paper proposes a mixed-model parallel twosided assembly line system that can be utilized to produce large-sized items in an inter-mixed sequence. The mixed-model parallel two-sided line balancing problem is defined and the advantages of utilizing multi-line stations across the lines are discussed. A flexible agent-based ant colony optimization algorithm is developed to solve the problem and a numerical example is given to explain the method systematically. The proposed algorithm builds flexible balancing solutions suitable for any model sequence launched. The dynamically changing workloads of workstations (based on specific product models during the production process) are also explored. A comprehensive experimental study is conducted and the results are statistically analyzed using the well-known paired sample t-test. The test results indicate that the mixed-model parallel two-sided assembly line system reduces the workforce need in comparison with separately balanced mixed-model two-sided lines. It is also shown that the proposed algorithm outperforms the tabu search algorithm and six heuristics often used in the assembly line balancing domain.  Section 3 has been re-written in elucidate manner. More explanations on acronyms used in Section 5.1 have been added for clarification. The manuscript has been carefully reviewed by an experienced proof-reader whose first language is English and who specializes in reviewing papers written by authors whose native language is not English.Our detailed responses to reviewer's comments have also been attached to this document.We hope that these revisions will be sufficient to make our manuscript suitable for publication in 'Computers & Industrial Engineering'. We believe that this study will become a base point for further works and yield more researches in this domain by attracting further interests from both academia and industry.We shall look forward to hearing from you at your earliest convenience. AbstractAssembly lines are frequently used as a production method to assemble complex products. Two-sided assembly lines are utilized to assemble large-sized products (e.g., Mixed-model Parallel Detailed Response to ReviewersOverall:The Authors have addressed all comments and queries, but still the paper needs some minor improvements. Response:Your comments are appreciated. All comments have been addressed individually and the blue font has been used in the revised paper to highlight the changes performed. Please find below the detailed responses to your comments. Comment-1:In proposed methodology, authors mentioned that heuristic and metaheuristic is used when it is hard to get solution, what does it mean? Response-1: Thank you for your comment. The sentence ...

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Mixed-model assembly line balancing in the make-to-order and stochastic environment using multi-objective evolutionary algorithms

Cited by 39 publications

References 15 publications

Balance horizontal de líneas de ensamble para modelos mixtos

Balance horizontal de líneas de ensamble para modelos mixtos

Research on Industrial Assembly Line Balancing Optimization Based on Genetic Algorithm and Witness Simulation

Mixed-model parallel two-sided assembly line balancing problem: A flexible agent-based ant colony optimization approach

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