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首页> 外文期刊>International Journal of Environmental Technology and Management >Optimal routing of complex transportation system of biomedical waste with multiple depot and disposal options
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Optimal routing of complex transportation system of biomedical waste with multiple depot and disposal options

机译:具有多个仓库和处置选项的生物医学废物复杂运输系统的优化路线

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摘要

Determination of safe and optimal routes for biomedical waste (BMW) collection and transportation using a fleet of vehicles is a complex issue. The issue gets significant, when the vehicles that outset from multiple depots, collects the BMW from hospitals scattered around a region and carry the waste to multiple disposal sites. The present paper deals with the development of a modified ACS-based approach to determine the optimal and safest route for BMW collection and transportation for such situation. The major objectives considered for route selection of vehicles, are the risk associated with the collection and transportation of BMW; total scheduling time of vehicles and number of vehicles. In this approach, clusters of the hospital nodes are constituted based on their distance from the nearest depot and late time window associated with the hospital node. Thereafter, the routes are scheduled and optimised using modified multi-objective ant colony system (MOACS). The computed results are validated abreast with benchmark solutions, demonstrating effectiveness of the proposed approach. Its applicability is elucidated using an illustrative example based on realistic data.
机译:使用车队确定生物医学废物(BMW)收集和运输的安全和最佳路线是一个复杂的问题。当从多个仓库开始的车辆从分散在一个地区的医院收集宝马并将废物运送到多个处置地点时,问题变得尤为严重。本文讨论了一种改进的基于ACS的方法的发展,以确定这种情况下BMW收集和运输的最佳和最安全的路线。车辆选路的主要目标是与宝马的收集和运输有关的风险;车辆的总调度时间和车辆数量。在这种方法中,医院节点的集群是基于它们距最近的仓库的距离和与医院节点相关联的延迟时间窗口而构成的。此后,使用改进的多目标蚁群系统(MOACS)对路线进行调度和优化。计算结果与基准解决方案并驾齐驱,证明了该方法的有效性。使用基于实际数据的说明性示例阐明了其适用性。

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