Assembly line balancing: Two resource constrained cases

International Journal of Production Economics (Impact Factor: 2.75). 02/2005; 96(1):129-140. DOI: 10.1016/j.ijpe.2004.03.008
Source: RePEc


In this paper, a new approach on traditional assembly line balancing problem is presented. The goal of proposed approach is to establish balance of the assembly line with minimum number of station and resources. For this purpose, 0–1 integer-programming models are developed. These models are solved using GAMS-CPLEX mathematical programming software for a numerical example.

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    • "However, there is a practical limitation on the value up to which a cycle time can be reduced. If the line balancing is not achieved within this practical limit alternative methods such as buffer stocks, shifting some of the operations to a new machine are to be considered [8]. "
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    ABSTRACT: Genetic Algorithm (GA) is an invaluable tool for solving optimization problems due to its robustness. It does not break even if the inputs are changed slightly or in the presence of a reasonable noise. GA offers a significant benefits over other optimization techniques in searching a large state space or n-dimensional surface In this paper we have made an attempt to study the effect of population size cross over and mutation on the performance and convergence of GA. The criteria for adopting the proper selection method is also studied. There is lot of literature on application of GA in various domains but best to our knowledge there exist very few papers which discuss the distribution of population, criteria for choosing selection method. Finally, we use the results for optimizing the non-value added cost component of a cycle time of constrained resources for productivity improvement. The problem is for medium scale manufacturing plant and is solved using GA toolbox of MATLAB. The results are used in redesigning the assembly line to overcome the limitations offered by constrained resources.
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    • "Simaria and Vilarinho (2007) developed an ant colony optimization algorithm for two sided assembly line balancing problem and the primary goal was to minimize the number of work stations. Agpak and Gokcen (2005) presented a new approach on assembly line balancing problem. They developed a mathematical formulation to the balancing assembly line to minimize the number of work stations and resources. "
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    ABSTRACT: One of the primary issues in line balancing problems is the uncertainty associated with the processing times. There are different reasons for having uncertain processing times such as task deterioration, failure in machines, etc. On the other hand, there are different objectives, such as cycle time, number of workstations in an assembly line balancing. In this paper, we present a multi-objective decision making assembly line balancing which minimizes different objectives such as cycle time and number of workstations. The resulted problem is formulated based on Lp-norm mixed integer programming and a meta-heuristic approach is also presented to solve the resulted model. The problem formulation is solved for some test examples and the results are discussed under different conditions.
    International Journal of Industrial Engineering Computations 10/2011; 2(4):863-872. DOI:10.5267/j.ijiec.2011.04.006
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    • "A significant variety of complex cases has been examined, including problems that consider lines with parallel workstations or parallel tasks; mixed or multi-models; multiple products; U-shaped, two-sided, buffered or parallel lines; incompatibility between tasks; stochastic processing times; and equipment selection –e.g., Park et al. (1997), Amen (2001, 2006), Ağpak and Gökçen (2005), Ding et al. (2006), Gamberini et al. (2006), Gökçen et al. (2006), Andrés et al. (2008), Capacho and Pastor (2008), Corominas et al. (2008), Capacho et al. (2009), Corominas and Pastor (2009), Cortés et al. (2009), Martino and Pastor (2010) and Pastor et al. (2010)–. As a result, generalized problems are becoming a widespread subject. "
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    ABSTRACT: The classic assembly line balancing problem (ALBP) basically consists of assigning a set of tasks to a group of workstations while maintaining the tasks' precedence relations. When the objective is to minimize the number of workstations m for a given cycle time CT , the problem is referred to as ALBP-1; if the objective is to minimize CT given m , then the problem is called ALBP-2. The only objective in ALBP-2 is to minimize CT , i.e., the workload of the most heavily loaded workstation (the bottleneck). However, considering the second-biggest, third-biggest, etc. workloads, can be important. Distributing a workload among six workstations as 10, 10, 10, 4, 3, 3, is not the same as distributing it as 10, 6, 6, 6, 6, 6. The CT value is the same, but the second distribution is beyond question more reliable and balanced. In this paper, we present and formalize a new assembly line balancing problem: the Lexicographic Bottleneck Assembly Line Balancing Problem (LB-ALBP). The LB-ALBP hierarchically minimizes the workload of the most heavily loaded workstation (CT), followed by the workload of the second most heavily loaded workstation, followed by the workload of the third most heavily loaded workstation, and so on. We present two mixed-integer linear programming (MILP) models designed to solve the LB-ALBP optimally, together with three heuristic procedures based on these MILPs.
    International Journal of Production Research 04/2011; 49(8). DOI:10.1080/00207541003705856 · 1.48 Impact Factor
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