Research on the Problem of MC Assembly Line Balancing Based on Genetic Algorithm

2006 ◽  
Vol 532-533 ◽  
pp. 1076-1079
Author(s):  
Shui Li Yang ◽  
Wei Ping Huang
Keyword(s):  
Genetic Algorithm ◽  
Mass Customization ◽  
Assembly Line ◽  
Assembly Line Balancing ◽  
Target Function ◽  
Optimal Solution ◽  
Idle Time ◽  
Line Balancing ◽  
Genetic Operators ◽  
Distribution Problems

Through the comparative analysis, the features of the mass customization assembly line are obtained. The corresponding genetic algorithm is designed with the total idle time and overloading time of the minimized assembly line as the target function, which is used to resolve the distribution problems of the operation elements in mass customization assembly line. The improved genetic operators can heighten the overall optimal solution ability of genetic algorithm convergence. The calculated examples indicate that this algorithm is the effective method for seeking out solution to the problems of operation elements in the mass customization assembly line.

A Method for Setting the Optimal Production Status Based on Genetic Algorithm in a Discrete Assembly System

2011 ◽  
Vol 421 ◽  
pp. 717-723
Author(s):  
Liang Dong ◽  
Zhen Guo Yan ◽  
Jie Zhang ◽  
Kun Peng Du ◽  
Yan Ping Wang
Keyword(s):  
Genetic Algorithm ◽  
Resource Utilization ◽  
Assembly Line ◽  
Assembly Line Balancing ◽  
Idle Time ◽  
Line Balancing ◽  
Assembly System ◽  
Utilization Rate ◽  
Optimal Production ◽  
General Flow

In a discrete assembly system, setting its optimal production status is one of the key works in assembly line balancing. Based on analyzing the objectives of assembly line control, a general flow for setting the optimal production status is proposed, and a method to identify rapidly the setting objects of production status is introduced. Then an optimal configuration solution for production status and its solving method in a station of an assembly line are established based on the genetic algorithm. At last, a wing assembly line is set as an example to validate this method, and the result shows that this method can provide a solution to optimize production status parameters for each station in this assembly line, which can reduce the resource idle time and cost, and so its resource utilization rate is improved.

Study and Analysis of GA-Based Heuristic Applied to Assembly Line Balancing Problem

2014 ◽  
Vol 13 (02) ◽  
pp. 113-131 ◽  
Author(s):  
P. Sivasankaran ◽  
P. Shahabudeen
Keyword(s):  
Cycle Time ◽  
Assembly Line ◽  
Assembly Line Balancing ◽  
Optimal Solution ◽  
Vital Role ◽  
Line Balancing ◽  
Problem Size ◽  
Minimum Number ◽  
Assembly Line Balancing Problem ◽  
Balancing Efficiency

Balancing assembly line in a mass production system plays a vital role to improve the productivity of a manufacturing system. In this paper, a single model assembly line balancing problem (SMALBP) is considered. The objective of this problem is to group the tasks in the assembly network into a minimum number of workstations for a given cycle time such that the balancing efficiency is maximized. This problem comes under combinatorial category. So, it is essential to develop efficient heuristic to find the near optimal solution of the problem in less time. In this paper, an attempt has been made to design four different genetic algorithm (GA)-based heuristics, and analyze them to select the best amongst them. The analysis has been carried out using a complete factorial experiment with three factors, viz. problem size, cycle time, and algorithm, and the results are reported.

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