具有混合车厢和时间窗的牛奶收集问题中多辆异构车辆的调度和路线

IF 4 3区 工程技术 Q2 ENGINEERING, INDUSTRIAL International Journal of Systems Science-Operations & Logistics Pub Date : 2023-04-17 DOI:10.1080/23302674.2023.2190852
Elmira Gheisariha, Farhad Etebari, Behnam Vahdani, Reza Tavakkoli-Moghaddam
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引用次数: 0

摘要

原料奶收集问题一直是乳制品和牛奶供应链的焦点,其中需要反映广泛的关注,包括协调异构车辆和在各种时间限制下协调各种活动。因此,本研究提供了一个具有不同牛奶质量的一般牛奶收集网络,以制定具有多个多室异构车辆的调度和路由问题,其中相关活动在不同的时间约束下进行,包括时间窗口,最大可用时间和计划范围。此外,还考虑了多车厢车辆的混合过程,以增加总利润为网络的主要目的。此外,提出了一种包含可变邻域搜索(VNS)和自适应大邻域搜索(ALNS)的混合元启发式算法来解决所提出的模型,其中开发了一种新的混合启发式算法来加速所提供的元启发式算法的混合过程。最后,通过实例分析和大量的数值实验来说明所提出的模型和求解方法的适用性和有效性。结果表明,混合工艺和多室车辆的考虑对系统的利润有显著影响。
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Scheduling and routing of multiple heterogeneous vehicles in a milk collection problem with blending in compartments and time windows
A raw milk collection problem is consistently the focus of the dairy and milk supply chain, wherein a broad range of concerns need to be reflected, including coordinating heterogeneous vehicles and harmonising various activities under miscellaneous time restrictions. So, this study offers a general milk collection network with different milk qualities to formulate a scheduling and routing problem with multiple multi-compartment heterogeneous vehicles, where associated activities are performed under various time constraints, including time windows, maximum available time, and planning horizon. Moreover, the blending process in multi-compartment vehicles is also considered to increase total profit as the primary purpose of the network. Additionally, a novel hybrid meta-heuristic algorithm that encompasses variable neighbourhood search (VNS) and adaptive large neighbourhood search (ALNS) is proposed to solve the proposed model, wherein a new heuristic algorithm for the blending process is developed to accelerate the offered meta-heuristic algorithm. Finally, a case study and extensive numerical experiments are offered to illustrate the applicability and validity of the proposed model and solution approach. The obtained results reveal that the considerations of the blending process and multi-compartment vehicles significantly impact the system's profit.
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来源期刊
CiteScore
7.60
自引率
16.70%
发文量
32
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