Balancing of mixed-model two-sided assembly lines

Özcan, Uğur; Toklu, Bilal

doi:10.1016/j.cie.2008.11.012

Cited by 147 publications

(99 citation statements)

References 34 publications

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“…Then, Ozcan et al (2011) and Hamzadayi and Yildiz (2012) proposed different genetic algorithm based approaches for balancing and sequencing of U-shaped lines simultaneously; by considering stochastic times, and parallel workstations -zoning constraints, respectively. Ozcan et al (2010b) and Kucukkoc and Zhang (2013) Simaria and Vilarinho (2009), Ozcan and Toklu (2009), and Chutima and Chimklai (2012 since there is no opportunity to utilise contrary stations (as in U-lines) or multi-line stations (as in parallel lines) and model mixes are not important unless a setup operation is required when changing from one model to another. However, Rabbani et al (2012) proposed multiple U-shaped layout to deal with mixed-model two-sided assembly line balancing problem and utilised contrary workstations.…”

Section: Literature Reviewmentioning

confidence: 99%

“…However, these two problems were dealt with separately by many researchers (i.e. Askin and Zhou (1997), Gokcen and Erel (1997), Vilarinho and Simaria (2002), McMullen and Tarasewich (2003), Haq et al (2006), Ozcan and Toklu (2009), Hamta et al (2013), , and Manavizadeh et al (2013a) for the line balancing problem; and Yano and Rachamadugu (1991), Bard et al (1992), Kim et al (1996), Zheng et al (2011), Bautista and Cano (2011), and Xu and Li (2013) for the model sequencing problem) with different objectives ever since the mixed-model line balancing problem was first introduced by Thomopoulos (1967).…”

Section: Introductionmentioning

confidence: 99%

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Mathematical model and agent based solution approach for the simultaneous balancing and sequencing of mixed-model parallel two-sided assembly lines

Küçükkoç

Zhang

2014

International Journal of Production Economics

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Cite this article as: Ibrahim Kucukkoc, David Z. Zhang, Mathematical model and agent based solution approach for the simultaneous balancing and sequencing of mixed-model parallel two-sided assembly lines, Int. J. Production Economics, http://dx.doi.org/10.1016/j.ijpe. 2014.08.010 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. AbstractOne of the key factors of a successfully implemented mixed-model line system is considering model sequencing problem as well as the line balancing problem. In the literature, there are many studies, which consider these two tightly interrelated problems individually. However, we integrate the model sequencing problem in the line balancing procedure to obtain a more efficient solution for the problem of Simultaneous Balancing and Sequencing of Mixed-Model Parallel Two-Sided AssemblyLines. A mathematical model is developed to present the problem and a novel agent based ant colony optimisation approach is proposed as the solution method. Different agents interact with each other to find a near optimal solution for the problem. Each ant selects a random behaviour from a predefined list of heuristics and builds a solution using this behaviour as a local search rule along with the pheromone value. Different cycle times are allowed for different two-sided lines located in parallel to each other and this yields a complex problem where different production cycles need to be considered to build a feasible solution. The performance of the proposed approach is tested through a set of test cases. Experimental results indicate that considering model sequencing problem with the line balancing problem together helps minimise line length and total number of required workstations. Also, it is found that the proposed approach outperforms other three heuristics tested.Keywords: mixed-model parallel two-sided assembly lines; simultaneous line balancing and model sequencing; agent based ant colony optimisation; production lines; metaheuristics; artificial intelligence. Experimental results indicate that considering model sequencing problem with the line balancing problem together helps minimise line length and total number of required workstations. Also, it is found that the proposed approach outperforms other three heuristics tested.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Mathematical model and agent based solution approach for the simultaneous balancing and sequencing of mixed-model parallel two-sided assembly lines

Küçükkoç

Zhang

2014

International Journal of Production Economics

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“…Ozcan and Toklu [22] presented a mathematical model and a simulated annealing algorithm for the solution of the problem. Chutima and Chimklai [23] developed a particle swarm optimisation algorithm with negative knowledge.…”

Section: Introductionmentioning

confidence: 99%

A nondominated sorting ant colony optimization algorithm for complex assembly line balancing problem incorporating incompatible task sets

Küçükkoç¹

2018

Pamukkale J Eng Sci

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“…At present, the researchers have proposed many fruitful methods to improve the balance and sequencing of the mixed flow line, such as the theoretical analysis method [7][8][9][10], the simulation method [11] and the combinatory method [12][13][14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

The Algorithm and Simulation of Multi-Objective Sequence and Balancing Problem for Mixed Mode Assembly Line

Yang¹,

Chen²,

Lin³

2017

Int. j. simul. model.

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In order to solve the balancing problem of product processing in a mixed flow assembly line, a modified genetic algorithm is proposed to optimize the instantaneous load and average load in the assembly line. An improved discrete particle swarm optimization algorithm is used to address the disordered and inefficient sequencing problem in processing products in an assembly line. Through a comprehensive consideration of the operating sequence, minimum production cycle, and the average load and instantaneous load of all workstations, the optimal solution was obtained and its load balancing conditions were studied. Based on the final solution and simulation results, the optimal solution was selected as the assembly line balancing alternative. The sequencing analysis result shows that by introducing the modified discrete PSO algorithm in the sequencing solution seeking in a mixed mode assembly line, the disordered and inefficient multi-objective sequencing problem can be effectively solved. According to the simulation result and calculated result, we set the ratio of the number of workstations to transmission rate as 10 and the product launch intervals as 45 s. Compared to the traditional algorithm, the improved algorithm has a smaller targeted function value, much shorter distance between the optimal solution and the ideal solution, and greater convergence capability.

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Balancing of mixed-model two-sided assembly lines

Cited by 147 publications

References 34 publications

Mathematical model and agent based solution approach for the simultaneous balancing and sequencing of mixed-model parallel two-sided assembly lines

Mathematical model and agent based solution approach for the simultaneous balancing and sequencing of mixed-model parallel two-sided assembly lines

A nondominated sorting ant colony optimization algorithm for complex assembly line balancing problem incorporating incompatible task sets

The Algorithm and Simulation of Multi-Objective Sequence and Balancing Problem for Mixed Mode Assembly Line

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