U-shaped assembly line worker assignment and balancing problem: A mathematical model and two meta-heuristics. (October 2017)

• Record Type: Journal Article
• Authors: Oksuz, Mehmet Kursat; Buyukozkan, Kadir; Satoglu, Sule Itir
• Is Part Of: Computers & industrial engineering. Volume 112(2017)
• Page Start: 246
• Page End: 263
• Publication Date: 2017-10
• Subjects: U-shaped assembly line -- Worker assignment -- Worker performance -- Heterogeneous workers -- Integer programming -- Artificial Bee Colony Algorithm -- Genetic Algorithm; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2017.08.030
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: Worker performance is considered during U-shaped assembly line balancing and worker assignment. A non-linear and a linearized model of the problem are formulated. To solve this problem, genetic and artificial bee colony algorithms are proposed. Problems of (Jackson, 1956) and (Cevikcan et. al., 2009) and data sets (Araújo et al. 2015) were solved. The artificial bee colony algorithm reached optimum solutions for all instances. Abstract: As the U-shaped assembly lines are concerned with manual assembly operations, workers' performance plays a major role. However, the past studies assume that all workers can carry out all tasks with an equal performance level, and actual task times do not depend on the worker who performs it. On the other hand, this is unrealistic. In this study, maximization of the line efficiency for the U-shaped assembly line worker assignment and balancing problem by considering the worker performance is aimed. First, a non-linear model of the problem is formulated, and then it is linearized. Later, an Artificial Bee Colony Algorithm and a Genetic Algorithm are proposed to solve it, in short computational times. A hypothetical data set (Jackson, 1956), a real data set (Cevikcan et al., 2009) and data sets of assembly line worker assignment and balancing problem (Araújo et al., 2015) were solved by using the model and the meta-heuristics. The meta-heuristics were able to reach solutions that have equal line efficiency with the optimum solution found by the proposed mathematical model. The contribution of this study is that the mathematical model for the U-shaped line assembly line worker assignment and balancing type-E problem that considers the workers' performance is formulated, and an Artificial Bee Colony Algorithm is proposed for the first time for this problem type.