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

- [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:**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:**Garment manufacturing is a traditional industry with global competition. The most critical manufacturing process is sewing, as it generally involves a great number of operations. The aim of assembly line balance planning in sewing lines is to assign tasks to the workstations, so that the machines of the workstation can perform the assigned tasks with a balanced loading. Assembly line balancing problem (ALBP) is known as an NP-hard problem. Thus, the heuristic methodology could be a better way to plan the sewing lines within a reasonable time.This paper develops a grouping genetic algorithm (GGA) for ALBP of sewing lines with different labor skill levels in garment industry. GGA can allocate workload among machines as evenly as possible for different labor skill levels, so the mean absolute deviations (MAD) can be minimized. Real data from garment factories and experimental design are used to evaluate GGA’s performance. Production managers can use the research results to quickly design sewing lines for important targets such as short cycle time and high labor utilization.Expert Systems with Applications 09/2012; 39(11):10073–10081. · 1.97 Impact Factor

Data provided are for informational purposes only. Although carefully collected, accuracy cannot be guaranteed. The impact factor represents a rough estimation of the journal's impact factor and does not reflect the actual current impact factor. Publisher conditions are provided by RoMEO. Differing provisions from the publisher's actual policy or licence agreement may be applicable.