New chance-constrained models for U-type stochastic assembly line balancing problem

2021 ◽  
Author(s):  
Mehmet Pınarbaşı
Keyword(s):  
Assembly Line ◽  
Assembly Line Balancing ◽  
Line Balancing ◽  
Assembly Line Balancing Problem ◽  
Constrained Models ◽  
Stochastic Assembly

EM ALGORITHM FOR SOLVING THE STOCHASTIC ASSEMBLY LINE BALANCING PROBLEM

2006 ◽  
Vol 39 (3) ◽  
pp. 419-424
Author(s):  
Liya Gu ◽  
Sophie Hennequin ◽  
Alexandru Sava ◽  
Xiaolan Xie
Keyword(s):  
Em Algorithm ◽  
Assembly Line ◽  
Assembly Line Balancing ◽  
Line Balancing ◽  
Assembly Line Balancing Problem ◽  
Stochastic Assembly

A multiple rule-based genetic algorithm for cost-oriented stochastic assembly line balancing problem

2019 ◽  
Vol 39 (1) ◽  
pp. 124-139 ◽  
Author(s):  
Ahad Foroughi ◽  
Hadi Gökçen
Keyword(s):  
Genetic Algorithm ◽  
Assembly Line ◽  
Assembly Line Balancing ◽  
Superior Performance ◽  
Line Balancing ◽  
Rule Based ◽  
Content Type ◽  
Assembly Line Balancing Problem ◽  
The Cost ◽  
Stochastic Assembly

Purpose This research aims to address the cost-oriented stochastic assembly line balancing problem (ALBP) and propose a chance-constrained programming model. Design/methodology/approach The cost-oriented stochastic ALBP is solved for small- to medium-sized problems. Owing to the non-deterministic polynomial-time (NP)-hardness problem, a multiple rule-based genetic algorithm (GA) is proposed for large-scale problems. Findings The experimental results show that the proposed GA has superior performance and efficiency compared to the global optimum solutions obtained by the IBM ILOG CPLEX optimization software. Originality/value To the best of the authors’ knowledge, only one study has discussed the cost-oriented stochastic ALBP using the new concept of cost. Owing to the NP-hard nature of the problem, it was necessary to develop a heuristic or meta-heuristic algorithm for large data sets; this research paper contributes to filling this gap.

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