Tackling the 1/3 variant of the time and space assembly line balancing problem by means of a multiobjective genetic algorithm

2011 ◽  
Author(s):  
Manuel Chica ◽  
Oscar Cordon ◽  
Sergio Damas
Keyword(s):  
Genetic Algorithm ◽  
Assembly Line ◽  
Assembly Line Balancing ◽  
Line Balancing ◽  
Time And Space ◽  
Multiobjective Genetic Algorithm ◽  
Assembly Line Balancing Problem

scholarly journals Time and space multi-manned assembly line balancing problem using genetic algorithm

2021 ◽  
Vol 14 (4) ◽  
pp. 733
Author(s):  
Nessren Zamzam ◽  
Ahmed Elakkad
Keyword(s):  
Genetic Algorithm ◽  
Assembly Line ◽  
Real Life ◽  
Assembly Line Balancing ◽  
Line Balancing ◽  
Initial Population ◽  
Time And Space ◽  
Task Time ◽  
Assembly Line Balancing Problem ◽  
Simple Assembly

Purpose: Time and Space assembly line balancing problem (TSALBP) is the problem of balancing the line taking the area required by the task and to store the tools into consideration. This area is important to be considered to minimize unplanned traveling distance by the workers and consequently unplanned time waste. Although TSALBP is a realistic problem that express the real-life situation, and it became more practical to consider multi-manned assembly line to get better space utilization, few literatures addressed the problem of time and space in simple assembly line and only one in multi-manned assembly line. In this paper the problem of balancing bi-objective time and space multi-manned assembly line is proposedDesign/methodology/approach: Hybrid genetic algorithm under time and space constraints besides assembly line conventional constraints is used to model this problem. The initial population is generated based on conventional assembly line heuristic added to random generations. The objective of this model is to minimize number of workers and number of stations.Findings: The results showed the effectiveness of the proposed model in solving multi-manned time and space assembly line problem. The proposed method gets better results in solving real-life Nissan problem compared to the literature. It is also found that there is a relationship between the variability of task time, maximum task time and cycle time on the solution of the problem. In some problem features it is more appropriate to solve the problem as simple assembly line than multi-manned assembly line.Originality/value: It is the first article to solve the problem of balancing multi-manned assembly line under time and area constraint using genetic algorithm. A relationship between the problem features and the solution is found according to it, the solution method (one sided or multi-manned) is defined.

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