Stochastic Local Search for Solving Chance-Constrained Multi-Manned U-shaped Assembly Line Balancing Problem with Time and Space Constraints

2021 ◽  
Vol 23 (04) ◽  
pp. 278-295
Author(s):  
Mohammad Zakarai ◽  
◽  
Hegazy Zaher ◽  
Naglaa Ragaa ◽  
◽  
...  
Keyword(s):  
Local Search ◽  
Assembly Line ◽  
Search Algorithm ◽  
Assembly Line Balancing ◽  
Fixed Number ◽  
Line Balancing ◽  
Benchmark Problems ◽  
Stochastic Local Search ◽  
Time And Space ◽  
Assembly Line Balancing Problem

The assembly line balancing problems have great importance in research and industry fields. They allow minimizing the learning aspects and guaranteeing a fixed number of products per day. This paper introduces a new problem that combines the multi-manned concept with the U-shaped lines with time and space constraints under uncertainty. The processing time of the tasks is considered as random variables with known means and variances. Therefore, chance-constraints appear in the cycle time constraints. In addition, each task has an associated area, where the assigned tasks per station are restricted by a total area. The proposed algorithm for solving the problem is a stochastic local search algorithm. The parameter levels of the proposed algorithm are optimized by the Taguchi method to cover the small, medium, and large-sized problems. Well-known benchmark problems have been adapted to cover the new model. The computational results showed the importance of the new problem and the efficiency of the proposed algorithm.

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.

Two-Sided Assembly Line Balancing Optimization With Spider Monkey Optimization

2020 ◽  
pp. 19-40
Author(s):  
Ashish Yadav ◽  
Sunil Agrawal
Keyword(s):  
Mathematical Model ◽  
Manufacturing Systems ◽  
Assembly Line ◽  
Assembly Line Balancing ◽  
Spider Monkey ◽  
Line Balancing ◽  
Benchmark Problems ◽  
Spider Monkey Optimization ◽  
Assembly Line Balancing Problem ◽  
Smo Algorithm

Growing interests from customers in customized products and increasing competition among peers necessitate companies to configure and balance their manufacturing systems more effectively than ever before. Two-sided assembly lines are usually constructed to produce large-sized high-volume products such as buses, trucks, automobiles, and some domestic products. Since the problem is well known as NP-hard problem, a mathematical model is solved by an exact solution-based approach and spider monkey optimization (SMO) algorithm that is inspired by the intelligent foraging behavior of fission-fusion social structure-based animals. In this chapter, the proposed mathematical model is applied to solve benchmark problems of two-sided assembly line balancing problem to minimize the number of mated stations and idle time. The experimental results show that spider monkey optimizations provide better results.

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