A note on “2-ANTBAL: An ant colony optimisation algorithm for balancing two-sided assembly lines”

Samouei, Parvaneh; Dezfoulian, Hamid Reza

doi:10.1016/j.cie.2017.06.002

Cited by 2 publications

(1 citation statement)

References 3 publications

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“…The second group includes studies using metaheuristic approaches. Genetic algorithm (Gurevsky et al, 2012;Alavidoost et al, 2015;Mura and Dini, 2016;Jusop and Rashid, 2016;Zhang et al, 2020), artificial bee colony algorithm (Tang et al, 2016;Zhao et al, 2016;Zhang et al, 2018), ant colony optimization (Zheng et al, 2012;Samouei and Dezfoulian, 2017;Huo et al, 2018;Huang et al, 2020), discrete cuckoo search , hybrid genetic algorithm (Lin et al, 2009), simulated annealing (Dong et al, 2018;, memetic algorithm (Pereira et al, 2018), fish school search algorithm (De Albuquerque et al, 2016); migrating birds optimization metaheuristic (Janardhanan et al 2019), multi-objective evolution strategies (Yoosefelahi et al, 2012;Zacharia & Nearchou, 2016).…”

Section: Literature Reviewmentioning

confidence: 99%

A linear physical programming model for assembly line balancing problem

Akpınar¹

2021

JER is an international, peer-reviewed journal that publishes f

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This paper deals with the mixed-model assembly line balancing problem. This type of line is applied to more than one similar model of a product in an intermixed order. Despite their widespread use, these lines have received little attention in the literature. Metaheuristics, heuristics and mathematical programming techniques are developed to solve these types of assembly line balancing problems. However, linear physical programming method has never used. In this paper, a linear physical programming model is proposed for balancing a mixed-model assembly line. The performance of the proposed model is applied to a numerical example to analyze the usage of the methodology. Five objectives are considered in the model and the outperformance of the methodology is demonstrated by comparing it to a different approach. According to the results, it has been seen that the proposed linear physical programming model is practical and useful approach for mixed-model assembly line balancing problems.

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