Bee algorithms for parallel two-sided assembly line balancing problem with walking times

Tapkan, Pınar; Özbakır, Lale; Baykasoğlu, Adil

doi:10.1016/j.asoc.2015.11.017

Cited by 45 publications

(18 citation statements)

References 39 publications

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“…Doğadan esinlenen algoritmaların yeni bir dalı olan sürü zekâsı yaklaşımı, böceklerin içgüdüsel problem çözme becerilerini kullanan etkili meta sezgisel yöntemler geliştirebilmek için böcek davranışlarının modellenmesine odaklanmıştır [15]. Sürü zekasına dayanan popülasyon temelli bir arama algoritması olan arı algoritmasının, genelleştirilmiş atama problemi [15], [16], montaj hattı dengeleme problemi [17], [18], iki boyutlu hücre oluşturma problemi [19] gibi bir çok farklı probleme başarıyla uygulanmış olmasına rağmen kübik hücre oluşturma problemine uygulanmamış olması dikkat çekicidir. Bu çalışmada kübik hücre oluşturma probleminin çözümü için arı algoritması (AA) ilk kez önerilmiştir.…”

Section: Figure 2 Three Dimensional (Cubic) Cell Formation Problemunclassified

Bees algorithm for cubic cell formation problem

Gökdaş¹,

Özçelik²

2020

Pamukkale J Eng Sci

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Hücre oluşturma problemi ile ilgili çalışmaların çoğunluğunda sadece parça ve makine ataması ele alınmaktadır. İşlerin makinelerde yapılması sırasındaki önemli rolü nedeniyle işçilerin hücrelere atanması, hücresel üretim sisteminden beklenen faydanın elde edilmesinde oldukça kritik bir faktör olmaktadır. İşçilerin ve makinelerin parça işlemedeki yeteneklerini dikkate almak, kaynakların verimliliğini ve esnekliği artırmada oldukça önemlidir. Bu çalışmada, üç boyutlu parça-makine-işçi temas matrisini dikkate alan kübik hücre oluşturma probleminin çözümü için arı algoritması geliştirilmiştir. Geliştirilen algoritma, hücre sayısının önceden bilindiği ve sabit olduğu literatürdeki diğer çalışmalardan farklı olarak, eniyi hücre sayısını belirleyebilmektedir. Arı algoritmasının performansı, literatürden alınan problemler kullanılarak test edilmiştir. Elde edilen sonuçlar, çözülen 11 problemin dokuzunda önerilen algoritmanın bilinen eniyi çözümlere ulaştığını ve kalan ikisinde de daha iyi çözümler bularak başarılı olduğunu göstermiştir. Hücre sayısının bilinmediği durumda ise problemlerin %100'ünde önerilen algoritma ile daha iyi çözümlere erişilmiştir.In the literature, most of the studies on cell formation problem only consider the assignment of parts and machines into the cells. Since workers have important role in doing jobs on machines, assignment of workers to cells becomes a crucial factor for fully utilization of cellular manufacturing systems. Considering the abilities of workers and the machines for processing parts are important to enhance flexibility and efficiency of resources. In this study, bees algorithm is developed to solve the cubic cell formation problem that considers the parts, the machines and the workers together while forming manufacturing cells. Unlike the methods in literature that define the number of cells as a constant number, the algorithm is capable of determining the optimum number of cells. The performance of the developed algorithm is tested by using problems from literature. The results showed that the proposed algorithm is able to find the best known solutions in nine out of 11 problems and better results for the remaining problems. For the case that the number of cells is not known, the algorithm improved the solutions for 100% of the problems.

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Section: Figure 2 Three Dimensional (Cubic) Cell Formation Problemunclassified

Bees algorithm for cubic cell formation problem

Gökdaş¹,

Özçelik²

2020

Pamukkale J Eng Sci

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“…The algorithm is an iterative process, so all operations are repeated until a certain number of iterations are obtained-it is presented in Algorithm 1. Make a mutation by Equation 5, 11:…”

Section: Genetic Algorithmmentioning

confidence: 99%

“…In [10], the author discussed a fusion of swarm methodology with neural networks for dynamic systems simulation and positioning. Parallel implementation of swarm methodology developed for two-sided line balancing problem was discussed in [11]. Massive-passing parallel approach to implement data tests were proposed in [12].…”

Section: Introductionmentioning

confidence: 99%

Parallel Technique for the Metaheuristic Algorithms Using Devoted Local Search and Manipulating the Solutions Space

et al. 2018

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The increasing exploration of alternative methods for solving optimization problems causes that parallelization and modification of the existing algorithms are necessary. Obtaining the right solution using the meta-heuristic algorithm may require long operating time or a large number of iterations or individuals in a population. The higher the number, the longer the operation time. In order to minimize not only the time, but also the value of the parameters we suggest three proposition to increase the efficiency of classical methods. The first one is to use the method of searching through the neighborhood in order to minimize the solution space exploration. Moreover, task distribution between threads and CPU cores can affect the speed of the algorithm and therefore make it work more efficiently. The second proposition involves manipulating the solutions space to minimize the number of calculations. In addition, the third proposition is the combination of the previous two. All propositions has been described, tested and analyzed due to the use of various test functions. Experimental research results show that the proposed methodology for parallelization and manipulation of solution space is efficient (increasing the accuracy of solutions and reducing performance time) and it is possible to apply it also to other optimization methods.

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“…Bee algorithms for Parallel TALBP with Walking Times [10] Introducing a two-sided assembly line problem with walking time.…”

Section: Discrete Artificial Bee Colony (Dabc)mentioning

confidence: 99%

Two-Sided assembly line balancing to minimize number of workstation with considering the relationships between tasks

2018

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There are many problems in assembly line. Some of the problems are assembly line reliability which relates to maintenance and unbalance workload. As a result, production line is not efficient and production plan is not fulfilled. Previous research on two-sided assembly line balancing problem has proprosed improvement method by considering index relationship between tasks. There are only two factors that is taken into account in this research, they are: distance factor of the implementation of the task (distance factor) and tools used to perform the task (tool factor). Therefore, this paper aims to develops conceptual model by considering additional factors that affecting Assembly Line Tasks Consistency (ATC). The additional factors that are considered are as follow: distance factor, tool factor, motion factor, layout factor, and skill factor. The purpose of this conceptual model is to increase productivity by minimizing number of workstations. Linear combination are used to find a combination solution of a relationship between task to complete a twosided assembly line balancing problem. Improvement of proposed assembly line are measured according to Balance Delay (BD) and Line Efficiency (LE).

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Bee algorithms for parallel two-sided assembly line balancing problem with walking times

Cited by 45 publications

References 39 publications

Bees algorithm for cubic cell formation problem

Bees algorithm for cubic cell formation problem

Parallel Technique for the Metaheuristic Algorithms Using Devoted Local Search and Manipulating the Solutions Space

Two-Sided assembly line balancing to minimize number of workstation with considering the relationships between tasks

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