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

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.

2019 ◽  
Vol 39 (1) ◽  
pp. 113-123 ◽  
Author(s):  
Han-ye Zhang

Purpose The purpose of this study is to develop an immune genetic algorithm (IGA) to solve the simple assembly line balancing problem of type 1 (SALBP-1). The objective is to minimize the number of workstations and workstation load for a given cycle time of the assembly line. Design/methodology/approach This paper develops a new solution method for SALBP-1, and a user-defined function named ψ(·) is proposed to convert all the individuals to satisfy the precedence relationships during the operation of IGA. Findings Computational experiments suggest that the proposed method is efficient. Originality/value An IGA is proposed to solve the SALBP-1 for the first time.


2019 ◽  
Vol 37 (2) ◽  
pp. 501-521 ◽  
Author(s):  
Masood Fathi ◽  
Amir Nourmohammadi ◽  
Amos H.C. Ng ◽  
Anna Syberfeldt ◽  
Hamidreza Eskandari

Purpose This study aims to propose an efficient optimization algorithm to solve the assembly line balancing problem (ALBP). The ALBP arises in high-volume, lean production systems when decision-makers aim to design an efficient assembly line while satisfying a set of constraints. Design/methodology/approach An improved genetic algorithm (IGA) is proposed in this study to deal with ALBP to optimize the number of stations and the workload smoothness. Findings To evaluate the performance of the IGA, it is used to solve a set of well-known benchmark problems and a real-life problem faced by an automobile manufacturer. The solutions obtained are compared against two existing algorithms in the literature and the basic genetic algorithm. The comparisons show the high efficiency and effectiveness of the IGA in dealing with ALBPs. Originality/value The proposed IGA benefits from a novel generation transfer mechanism that improves the diversification capability of the algorithm by allowing population transfer between different generations. In addition, an effective variable neighborhood search is used in the IGA to enhance its local search capability.


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