An artificial immune system algorithm for solving the stochastic multi-manned assembly line balancing problem

Mohammad Zakaraia, Hegazy Zaher and Naglaa Ragaa

International Journal of Industrial and Systems Engineering, 2023, vol. 45, issue 1, 68-88

Abstract: In recent years, there has been an increasing interest in the multi-manned assembly line balancing problem (MALBP). It introduces the concept of assigning more operators at the same station to minimise the line length and to increase the production rate. Most of the previous works did not discuss such problems under uncertainty. Therefore, this paper presents a chance-constrained programming model that considers the processing times of the tasks as normally distributed random variables with known means and variances. The proposed algorithm for solving the problem is an artificial immune system algorithm. To get optimised results from the proposed algorithm, the parameters are tuned using a design of experiments. The computational results show the implementation of the proposed algorithm on 70 problems taken from well-known benchmarks in case that chance probability is equal to 0.95, 0.95, and 0.975.

Keywords: MALBP; chance-constrained programming; artificial immune system; AIS; Taguchi orthogonal arrays; analysis of variance; ANOVA; Tukey's HSD test. (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:ids:ijisen:v:45:y:2023:i:1:p:68-88

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