Simultaneous solving of balancing and sequencing problems in mixed-model assembly line systems

Mosadegh, Hadi; Ghomi, S. M. T. Fatemi; Zandieh, M.

doi:10.1080/00207543.2011.625559

Cited by 14 publications

(6 citation statements)

References 33 publications

(36 reference statements)

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“…Hence, the simultaneous consideration of both decisions is only viable under very special conditions (Hwang and Katayama 2010;Kucukkoc and Zhang 2014;Lian et al 2012;Mosadegh, Ghomi, and Zandieh 2012). When a MAL is balanced, it is difficult to evaluate the system throughput because the line may encounter blockage and starvation at the subsequent sequencing stage due to station variability.…”

Section: Literature Reviewmentioning

confidence: 99%

Balancing mixed-model assembly lines with adjacent task duplication

Yang

Gao

2014

International Journal of Production Research

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When a mixed-model assembly line (MAL) is balanced, it is generally assumed that the variants of a task over different models should be assigned to an identical station. In this study, this restriction is relaxed and the variants of a task over different models can be duplicated on two adjacent stations (referred to as adjacent task duplication) to improve the MAL's efficiency. The adjacent task duplication incurs few additional training and tool duplication costs as each task is duplicated on at most two stations. Moreover, for each task, the assembly part storage is not duplicated as it can be shared by the two adjacent stations. The mathematical model of this problem is formulated and some important properties are characterised. A branch, bound and remember algorithm is then developed to solve the problem. The performance of the proposed algorithm is tested on 900 representative instances, of which 889 instances are optimally solved. The experimental results show that the use of the adjacent task duplication policy effectively reduces the number of stations, especially when the WEST ratios are small. IntroductionAssembly lines are flow-oriented production systems that are typical in the industrial production of high-quantity standardised commodities (Becker and Scholl 2006). The labour productivity of assembly lines is largely driven by how the tasks (indivisible elements of work) are assigned to stations subject to technological constraints, commonly referred to as assembly line balancing (ALB) (Battaïa and Dolgui 2013). The simple assembly line balancing problem (SALBP) aims to minimise the number of stations given the cycle time (type I) or the cycle time given the number of stations (type II) (Baybars 1986).The mixed-model assembly line (MAL) is a more complex environment in which several product models are assembled simultaneously in intermixed sequences (Thomopoulos 1967). MALs are widely used in many industries such as automobiles, white goods and consumer electronics, where demand is characterised by high variability and relatively small volume for each model (Becker and Scholl 2006). A MAL generally assembles different versions of one basic product rather than completely different items. Hence, many studies assume that a single precedence diagram can be drawn to resume the precedence relationships among different tasks over each model (Merengo, Nava, and Pozzetti 1999). However, the processing time of a task may differ over the various models, and each variant of the task over these models should be regarded as a separate work element (Boysen, Fliedner, and Scholl 2008). The MAL balancing problem (MALBP) involves assigning all the task variants to stations.A straightforward approach for modelling and solving MALBPs is to restrict all the variants of a task over different models to an identical station. This restriction is reasonable, considering that these task variants may require the same skills, tools or assembly parts (Thomopoulos 1967). With this restriction, MALBPs are reduced to some version of...

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Section: Literature Reviewmentioning

confidence: 99%

Balancing mixed-model assembly lines with adjacent task duplication

Yang

Gao

2014

International Journal of Production Research

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“…Mosadegh et al, but they did not consider some realistic constraints, and only considered the normal distribution of task time. [18] implemented a simple SA algorithm to solve the balancing and sequencing problems in the mixed-model assembly line (MMAL), But he did not conduct research on the uncertain assembly time. Pinar Tapkan et al [19] employed bees algorithm and artificial bee colony algorithm for parallel two-sided assembly line balancing problem with walking times.…”

Section: Literature Reviewmentioning

confidence: 99%

Solving Multi-Objective Two-Sided Assembly Line Balancing Problems by Harmony Search Algorithm Based on Pareto Entropy

Zheng¹,

Ning

Sun

et al. 2021

IEEE Access

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Two-sided assembly lines are designed to produce large and complex products, where workers can perform on both sides at the same time. This paper establishes a mathematical model for the multi-objective two-sided assembly line balancing problems with additional constraints (MOATALBP). The model considers both workers' skill and balance of the assembly line, aimings to maximize efficiency and minimize the workers cost and smoothness index. A harmony search algorithm(HS) based on Pareto entropy (PE-MHS) is proposed to solve MOATALBP. The difference entropy of Pareto solutions is employed to adjust algorithm parameters to enhance optimization ability of PE-MHS. Moreover, the finetuning operation combining insertion and inverse sequence is utilized to avoid the algorithm falling into local optima. Ultimately, non-dominated sorting ensures a set of well-distributed Pareto solutions. The experimental results of different problems indicate that the proposed algorithm can achieve better solutions than three classical algorithms (NSGAII, SPEA2 and HS) for the MOATALBP. INDEX TERMSHarmony search algorithm, multi-objective optimization, pareto entropy, two-sided assembly line balancing.

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“…(6) The processing of a product in a given station cannot finish unless all jobs of that product currently being processed at that station are completed; (7) The jobs of a product are transferred from one station to another following the precedence relations and the revisiting of stations is not allowed;…”

Section: Problem Definitionmentioning

confidence: 99%

“…Therefore, to consider both problems simultaneously in the same time frame is a new tendency in MMAL literature. For example, Mosadegh et al [7] proposed integrated approaches to MMAL balancing and sequencing. However, simultaneous approach to assembly line balancing and scheduling problems brings new computational challenges, especially as the problem instance grows.…”

Section: Introductionmentioning

confidence: 99%

Integrated Approach for Flexible Mixed Model Assembly Lines Balancing and Model Sequencing Problem

Bai

Pang³

2014

AMM

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The manufacturers nowadays are forced to respond very quickly to changes in the market conditions. To adopt flexible mixed model assembly lines (MMAL) is a preferred way for manufacturers to improve competitiveness. Managing a mixed model assembly line involves two problems: assigning assembly tasks to stations (balancing problem) and determining the sequence of products at each station (sequencing problem). In order to solve both balancing and sequencing problem in MMAL simultaneously, an integrated mathematical model based on mixed integer programming (MIP) is developed to describe the problem. In the model, general type precedence relations and task duplications are considered. Due to the NP-hardness of the balancing and sequencing problem of MMAL, GA is designed to search the optimal solution. The efficiency of the GA is demonstrated by a case study.

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Simultaneous solving of balancing and sequencing problems in mixed-model assembly line systems

Cited by 14 publications

References 33 publications

Balancing mixed-model assembly lines with adjacent task duplication

Balancing mixed-model assembly lines with adjacent task duplication

Solving Multi-Objective Two-Sided Assembly Line Balancing Problems by Harmony Search Algorithm Based on Pareto Entropy

Integrated Approach for Flexible Mixed Model Assembly Lines Balancing and Model Sequencing Problem

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