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对于在制造车间环境中执行多种运输任务的多重载荷自动驾驶车辆,节能路径规划

Zhongwei Zhang¹, Lihui Wu², Boqiang Zhang³

¹Henan Key Laboratory of Superhard Abrasives and Grinding Equipment, Henan University of Technology, Zhengzhou, 450001, China.

Environmental science and pollution research international

|March 14, 2024

概括

本研究介绍了制造业中自动引导车辆 (AGV) 的节能路径规划模型. 该模型优化了多重载荷AGV的运输距离和能源消耗,提高了物流的可持续性.

科学领域:

物流和供应链管理的物流和供应链管理.
运营研究运营研究
机器人和自动化机器人和自动化

背景情况:

自动引导车辆 (AGV) 对于制造业的智能物流至关重要.
有效的路径规划对于优化AGV运营和可持续性至关重要.
多重载荷 AGV 在任务执行和能源管理方面提出了独特的挑战.

研究的目的:

为制造车间的多重载荷 AGV 开发一个节能路径规划模型.
优化运输距离和能源消耗 (EC) 作为双重目标.
通过智能AGV路由来提高物流流程的可持续性.

主要方法:

提出了一种两阶段的方法来解决能源效率路径规划问题.
阶段1:采用车间的拓地图,获取节点之间的最佳能效路径.
第二阶段:使用非主导排序基因算法-II (NSGA-II) 来确定最佳的任务序列和路径选择.

主要成果:

建立的模型证明了多重负载AGV的显著节能效应.
提出的两阶段解决方案方法在优化AGV运营方面被证明是有效的.
分析确定了影响多重负载AGV能源消耗的关键因素.

结论:

开发的节能路径规划模型提高了基于AGV的物流的可持续性.
基于NSGA-II的两阶段方法为复杂的多重负载AGV路由问题提供了有效的解决方案.
了解影响AGV EC的因素对于进一步优化智能制造环境至关重要.

关键词:

能源消耗能源消耗是指能源的消耗.节能路径规划节能路径规划制造车间制造车间制造车间多重载荷自动引导车辆多重载荷自动引导车辆多重的运输任务多重的运输任务非主导分类的遗传算法-IIII

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