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

被引:0
|
作者
Zakaraia M. [1 ]
Zaher H. [1 ]
Ragaa N. [1 ]
机构
[1] Faculty of Graduate Studies for Statistical Research, Cairo University, 5 Ahmed Zewail, Ad Doqi, Giza Governorate, Dokki
关键词
AIS; analysis of variance; ANOVA; artificial immune system; chance-constrained programming; MALBP; Taguchi orthogonal arrays; Tukey’s HSD test;
D O I
10.1504/IJISE.2023.133527
中图分类号
学科分类号
摘要
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. Copyright © 2023 Inderscience Enterprises Ltd.
引用
收藏
页码:68 / 88
页数:20
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