基于遗传算法的客户不容忍Markovian模型的成本优化

IF 1.5 Q3 ENGINEERING, MULTIDISCIPLINARY
Anamika Jain, Chandrima Raychaudhuri
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引用次数: 0

摘要

在本文中,我们考虑了一个具有工作假期和多个工作故障的单服务器排队模型。度假时,服务器以不同的速度工作。由于多次故障,服务器会出现干扰。在工作故障中,服务器以不同的速度工作。在工作休假和工作故障导致的中断期间,主服务器可以找到许多正在运行的实现。服务器的使用寿命和修复时间都被认为是呈指数分布的。此外,我们还考虑了客户的犹豫和反悔行为。使用矩阵分析技术来计算平稳队列长度分布。利用遗传算法对成本函数进行了优化。繁忙期的预测长度、工作休假期的预期长度、工作故障期的预期时间、平均等待时间和平均延迟都已确定。我们计算了数值结果来验证分析观点。使用灵敏度分析来研究各个参数的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cost Optimization using Genetic Algorithm in Customers Intolerance Markovian Model with Working Vacation and Multiple Working Breakdowns
In this paper we consider a single server queueing model with working vacation and multiple working breakdowns. When on vacation, the server works at a different pace. Disturbances occur in the server due to multiple breakdowns. In working breakdowns server works at a different rate. During the time of interruption caused by working vacation and working breakdowns, the main server can find many implementations in operation. Both the server's lifespan and the time it takes to repair it are considered to be exponentially dispersed. Also, we have considered balking and reneging behaviours of customers. The stationary queue length distribution is computed using a matrix-analytic technique. Using Genetic Algorithm (GA) we optimize the cost function. The predicted length of a busy period, the expected length of a working vacation period, the expected length of a working breakdown period, the mean waiting time, and the average delay are all established. We compute numerical results to verify the analytical point of view. The effect of individual parameters is investigated using sensitivity analysis.
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来源期刊
CiteScore
3.80
自引率
6.20%
发文量
57
审稿时长
20 weeks
期刊介绍: IJMEMS is a peer reviewed international journal aiming on both the theoretical and practical aspects of mathematical, engineering and management sciences. The original, not-previously published, research manuscripts on topics such as the following (but not limited to) will be considered for publication: *Mathematical Sciences- applied mathematics and allied fields, operations research, mathematical statistics. *Engineering Sciences- computer science engineering, mechanical engineering, information technology engineering, civil engineering, aeronautical engineering, industrial engineering, systems engineering, reliability engineering, production engineering. *Management Sciences- engineering management, risk management, business models, supply chain management.
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