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Multiple Objective Optimization of Green Logistics Using Cuckoo Searching Algorithm

机译:使用杜鹃搜索算法的绿色物流多目标优化

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摘要

Green Logistics becomes critical in Supply Chain Management due to it having less of an impact to the environment.udGreen Logistics optimization refers to the determination depot quantity, decreasing uncovered demand and CO2 emission reduction. To date, application of Cuckoo searching algorithm has been proven to be very efficient and reliable in solving optimization problems; it is also capable of operating simultaneously with multiple solutions. Basically, Cuckoo searching algorithm imitates the natural evolution of a population with initial solutions. In this paper, a modified Cuckoo searchingudalgorithm is proposed to solve the multiple objective Green Logistics optimization problem. MATLAB software is used toudvalidate and evaluate the proposed model. This work forms the basis for solving many other similar problems that occur in manufacturing and service industries. The final solution to this multiple objective problem is reached by using a set of Pareto solutions.
机译:绿色物流由于对环境的影响较小,因此在供应链管理中变得至关重要。 ud绿色物流优化是指确定仓库数量,减少未发现的需求量和减少CO2排放量。迄今为止,已经证明了杜鹃搜索算法在解决优化问题方面非常有效和可靠。它还能够与多种解决方案同时运行。基本上,布谷鸟搜索算法使用初始解来模拟种群的自然进化。为了解决多目标绿色物流优化问题,提出了一种改进的布谷鸟搜索算法。 MATLAB软件用于验证和评估所提出的模型。这项工作为解决制造业和服务业中发生的许多其他类似问题奠定了基础。通过使用一组Pareto解决方案,可以解决此多目标问题的最终解决方案。

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    Wang Wei; Liu Yao;

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  • 年度 2016
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