Article

# Assembly line balancing: Two resource constrained cases

International Journal of Production Economics (Impact Factor: 2.08). 02/2005; 96(1):129-140. DOI: 10.1016/j.ijpe.2004.03.008

Source: RePEc

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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.International Journal of Latest Trends in Engineering and Technology (IJLTET) Special Issue. 10/2013; - [Show abstract] [Hide abstract]

**ABSTRACT:**This paper addresses a novel approach to deal with Flexible task Time Assembly Line Balancing Problem (FTALBP). In this regard, machines are considered in which operation time of each task can be between lower and upper bounds. These machines can compress the processing time of tasks, but this action may lead to higher cost due to cumulative wear, erosion, fatigue and so on. This cost is described in terms of task time via a linear function. Hence, a bi-criteria nonlinear integer programming model is developed which comprises two inconsistent objective functions: minimizing the cycle time and minimizing the machine total costs. In order to sustain these objectives concurrently, this paper applies the LP-metric method to make a combined dimensionless objective. Moreover, a genetic algorithm (GA) is presented to solve this NP-hard problem and design of experiments (DOE) method is hired to tune various parameters of our proposed algorithm. The computational results demonstrate the effectiveness of implemented procedures.Applied Mathematical Modelling 12/2011; 35(12):5592-5608. · 2.16 Impact Factor - [Show abstract] [Hide abstract]

**ABSTRACT:**The Lexicographic Bottleneck Assembly Line Balancing Problem (LB-ALBP) is a new assembly-line balancing problem recently defined in the literature. The LB-ALBP hierarchically minimises the workload of the most heavily loaded workstation, 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. The original study presents two mixed-integer linear programming (MILP) models designed to solve the LB-ALBP optimally, together with three heuristic procedures based on these MILPs. In this paper, we propose and test new algorithms that combine a heuristic procedure for obtaining an initial solution and several local search procedures, which are an improvement upon the heuristic procedures published to date.International Journal of Production Research 01/2011; · 1.46 Impact Factor

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