Hybridizing ant colony optimization via genetic algorithm for mixed-model assembly line balancing problem with sequence dependent setup times between tasks

Akpınar, Şener; Bayhan, G. Miraç; Baykasoğlu, Adil

doi:10.1016/j.asoc.2012.07.024

Cited by 109 publications

(50 citation statements)

References 44 publications

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“…Since then, these two meta-heuristics have attracted researchers and been [59], Chen and Chien [60], Li et al [61], and Akpinar et al [5]. Among these hybridization techniques, the method of Akpinar et al [5] was used to solve MALBP with sequence dependent setup times between tasks.…”

Section: The Proposed Methodsmentioning

confidence: 99%

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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Section: The Proposed Methodsmentioning

confidence: 99%

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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“…Son olarak, Akpınar ve diğ. [26], paralel istasyonlu, bölgeleme kısıtlı ve işler arasında sıraya bağımlı olmayan hazırlık zamanlarının olduğu problem için bir melez sezgisel yaklaşım önermişlerdir. Önerilen yaklaşım, genetik algoritma ve karınca koloni optimizasyonu algoritmasına dayanmaktadır.…”

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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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“…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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Hybridizing ant colony optimization via genetic algorithm for mixed-model assembly line balancing problem with sequence dependent setup times between tasks

Cited by 109 publications

References 44 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

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

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