Balancing mixed-model assembly lines to reduce work overload

Matanachai, Sittichai; Yano, Candace Arai

doi:10.1080/07408170108936804

Cited by 46 publications

(36 citation statements)

References 23 publications

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“…This process continues until all tasks are assigned. [5,4,7], [5,9,10], [8,7,12], [3,6,8], [9,10,13,16], [], [11,12], [11,14,15], []]…”

Section: Simulation Of the Solution Proceduresmentioning

confidence: 99%

“…C C A B F D E [ [1,4,3,6], [2,5,7], [1,4,7], [2,5,10], [9,11], [8,10,12], [3,6,8,16], [9,13] [3,2], [2,3,6], [1,5,4,7], [9,11], [5,8,7,10,15], [8,12,16], [10,9,11,13,14], [], [12],…”

mentioning

confidence: 99%

“…C C A B D F E [ [3,1,6,4,7], [2,5], [2,3,6], [1,4,5,7], [], [9,11,12], [8,11,13], [10,14,9], [], [8,10], [16,12,15], []]…”

mentioning

confidence: 99%

“…C A B C F E D [ [1,6,4], [3,2], [1,4,7], [2,5,9], [5,11], [9,7,8], [3,6,12], [10,13,16,8], [], [10,12], [11,15,14], []]…”

mentioning

confidence: 99%

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Integrating ant colony and genetic algorithms in the balancing and scheduling of complex assembly lines

Küçükkoç

Zhang

2015

Int J Adv Manuf Technol

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Usage guidelinesThis version is made available online in accordance with publisher policies. To see the final version of this paper, please visit the publisher's website (a subscription may be required to access the full text).Before reusing this item please check the rights under which it has been made available. Some items are restricted to non-commercial use. Please cite the published version where applicable. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final 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. Different from a large number of existing studies in the literature, this paper addresses two important issues in managing production lines, the problems of line balancing and model sequencing, concurrently. A novel hybrid agent based ant colony optimization -genetic algorithm approach is developed for the solution of mixed-model parallel two-sided assembly line balancing and sequencing problem. The existing agent based ant colony optimization algorithm is enhanced with the integration of a new genetic algorithm based model sequencing mechanism. The algorithm provides ants the opportunity of selecting a random behavior among ten heuristics commonly used in the line balancing domain. A numerical example is given to illustrate the solution building procedure of the algorithm and the evolution of the chromosomes. The performance of the developed algorithm is also assessed through test problems and analysis of their solutions through a statistical test, namely Paired-Sample tTest. In accordance with the test results, it is statistically proven that the integrated genetic algorithm based model sequencing engine helps agent based ant colony optimization algorithm robustly find significantly better quality solutions.

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“…This process continues until all tasks are assigned. [5,4,7], [5,9,10], [8,7,12], [3,6,8], [9,10,13,16], [], [11,12], [11,14,15], []]…”

Section: Simulation Of the Solution Proceduresmentioning

confidence: 99%

“…C C A B F D E [ [1,4,3,6], [2,5,7], [1,4,7], [2,5,10], [9,11], [8,10,12], [3,6,8,16], [9,13] [3,2], [2,3,6], [1,5,4,7], [9,11], [5,8,7,10,15], [8,12,16], [10,9,11,13,14], [], [12],…”

mentioning

confidence: 99%

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Integrating ant colony and genetic algorithms in the balancing and scheduling of complex assembly lines

Küçükkoç

Zhang

2015

Int J Adv Manuf Technol

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“…Bu problem için Erel ve Gokcen [16] tarafından bir en-kısa rota formülasyonu önerilmiştir. Matanachai ve Yano [17], dengeli iş yükleri sağlayacak şekilde bir sezgisel yöntem tanımlamışlardır. Vilarinho ve Simaria [18], paralel istasyonlu ve stokastik işlem süreli karışık-modelli montaj hattı dengeleme problemi için matematiksel model ve tavlama benzetimine dayanan iki aşamalı bir sezgisel sunmuşlardır.…”

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Yasak Arama Algori̇tmasina Dayali Pürüzsüzleşti̇rme Yaklaşimi İçeren Karişik-Modelli̇ Montaj Hatti Dengeleme

Yağmahan¹,

Emel²

2015

Gazi Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi

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ÖZETKarışık-modelli montaj hatları, çeşitli modellerde talep edilen ürünlerin daha ucuz olacak şekilde montajı için kullanılır. Bu tür hatlar tasarlandığında, montaj hattının zaman, yer, konum vb. kısıtlar altında daha verimli ve düzenli bir şekilde çalışabilmesi için, istasyonlardaki işlemlerin dengelenmesi gerekir. Bu makalede, karışık-modelli montaj hattı dengeleme problemi için belli bir çevrim süresine karşılık istasyon sayısının minimizasyonunu amaçlayan bir sezgisel algoritma geliştirilmiştir. Ayrıca önerilen bir yasak arama algoritmasına dayalı pürüzsüzleştirme yaklaşımı ile istasyonlarda modellere ait ortak işlemlerdeki süre farklılıklarından kaynaklanan dengesizlikler giderilmeye çalışılmıştır.Anahtar Kelimeler: Karışık-model, montaj hattı dengeleme, yasak arama, pürüzsüzleştirme MIXED-MODEL ASSEMBLY LINE BALANCING WITH SMOOTHING APPROACH BASED ON TABU SEARCH ALGORITHM ABSTRACTMixed-model assembly lines are needed for the assembly of products with a variety of models at comparatively lower costs. The design of such lines requires the work to be done at stations well balanced, satisfying the constraints such as time, space and location for optimal productivity and efficiency. This paper presents a heuristic algorithm for the mixed-model assembly line balancing problem to minimize the number of stations for a given cycle time. The proposed algorithm further reduces time discrepancies among stations due to differences in times for common operations of different models by using a smoothing approach which is based on the tabu search algorithm.

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A balancing problem for mixed model assembly lines with a paced moving conveyor

Zhao¹,

Ohno²,

Lau³

2004

Naval Research Logistics

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Abstract:We state a balancing problem for mixed model assembly lines with a paced moving conveyor as: Given the daily assembling sequence of the models, the tasks of each model, the precedence relations among the tasks, and the operations parameters of the assembly line, assign the tasks of the models to the workstations so as to minimize the total overload time. Several characteristics of the problem are investigated. A line-balancing heuristic is proposed based on a lower bound of the total overload time. A practical procedure is provided for estimating the deviation of any given line-balance solution from the theoretical optimum. Numerical examples are given to illustrate the methodology.

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Balancing mixed-model assembly lines to reduce work overload

Cited by 46 publications

References 23 publications

Integrating ant colony and genetic algorithms in the balancing and scheduling of complex assembly lines

Integrating ant colony and genetic algorithms in the balancing and scheduling of complex assembly lines

Yasak Arama Algori̇tmasina Dayali Pürüzsüzleşti̇rme Yaklaşimi İçeren Karişik-Modelli̇ Montaj Hatti Dengeleme

A balancing problem for mixed model assembly lines with a paced moving conveyor

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