Performance analysis of supply chain network using a genetic algorithm and simulation

S. Kumanan; S. Prasanna Venkatesan; K. Kumar; J. Prasanna Kumar

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Performance analysis of supply chain network using a genetic algorithm and simulation

机译：基于遗传算法和仿真的供应链网络绩效分析

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Globalisation of economies and technological developments in information systems are forcing enterprises to re-orient their business strategies from independent operations towards integrated, strategic partnerships. This redirection has resulted in the evolution of the supply chain. The supply chain analysis tools and methodologies are improved for effective and efficient decision-making. In this paper, a genetic algorithm is proposed and exemplified for optimising the distribution plan of a two-stage supply chain logistic network. The outcome of the GA methodology is used in a simulation model developed to analyse the influence of demand fluctuation. Case examples are presented with the results and discussion.

机译：经济全球化和信息系统的技术发展正迫使企业重新调整其业务战略，从独立运营转向综合战略伙伴关系。这种重定向导致了供应链的发展。供应链分析工具和方法得到了改进，以进行有效的决策。提出并举例说明了一种遗传算法，用于优化两阶段供应链物流网络的分配计划。 GA方法的结果用于模拟模型中，以分析需求波动的影响。案例示例与结果和讨论一起呈现。

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来源
《International journal of agile systems and management》 |2006年第4期|p.450-462|共13页
作者
S. Kumanan; S. Prasanna Venkatesan; K. Kumar; J. Prasanna Kumar;
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作者单位

Department of Production Engineering National Institute of Technology Tiruchirappalli, TamilNadu, India;

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原文格式 PDF
正文语种 eng
中图分类计算技术、计算机技术;
关键词
supply chain optimisation; genetic algorithm (GA); customer responsiveness; distribution planning; spreadsheet simulation;

机译：供应链优化;遗传算法;客户响应度;分销计划;电子表格模拟;

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1. Maximisation of total supply chain profit and minimisation of bullwhip effect in a multi-echelon supply chain network using particle swarm optimisation and genetic algorithm [J] . Nafisa Mahbub, Ahsan Akhtar Hasin, Ridwan Al Aziz, International Journal of Integrated Supply Management . 2017,第2a3期

机译：利用粒子群优化和遗传算法，多梯队供应链网络中总供应链利润和最小化牛鞭效应的最大化
2. A risk-based optimization framework for integrated supply chains using genetic algorithm and artificial neural networks [J] . Nezamoddini Nasim, Gholami Amirhosein, Aqlan Faisal International journal of production economics . 2020,第Jula期

机译：遗传算法和人工神经网络的集成供应链的基于风险的优化框架
3. Neural Networks and Genetic Algorithms Applied for Implementing the Management Model “Triple A” in a Supply Chain. Case: Collection Centers of Raw Milk in the Azuay Province [J] . Bermeo M. Juan Pablo1, CastilIo C. Hilda Piedad2, Serrano V. Santiago3 MATEC Web of Conferences . 2016,第2016期

机译：神经网络和遗传算法在供应链中用于实施“ Triple A”管理模型。案例：阿苏耶省原奶收集中心
4. STABILITY ANALYSIS OF THE SUPPLY CHAIN BY USING NEURAL NETWORKS AND GENETIC ALGORITHMS [C] . Alfonso Sarmiento, Luis Rabelo, Ramamoorthy Lakkoju, Simulation Conference . 2007

机译：利用神经网络和遗传算法供应链的稳定性分析
5. Design and analysis of supply chain networks using genetic algorithms and numerical clustering. [D] . Srinivasan, Mukundan. 2000

机译：使用遗传算法和数值聚类设计和分析供应链网络。
6. Hybrid Algorithms for Fuzzy Reverse Supply Chain Network Design [O] . Z. H. Che, Tzu-An Chiang, Y. C. Kuo, -1

机译：模糊逆供应链网络设计的混合算法
7. STABILITY ANALYSIS OF THE SUPPLY CHAIN BY USING NEURAL NETWORKS AND GENETIC ALGORITHMS [O] . S. G. Henderson, B. Biller, M. -h. Hsieh, 2010

机译：基于神经网络和遗传算法的供应链稳定性分析

Performance analysis of supply chain network using a genetic algorithm and simulation

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