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    Dynamic vehicle routing problem with industry 4.0 approach

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    diss. embargoed till 2022-12-31 (1.415Mb)
    Date
    2021-12
    Author
    Abdirad, Maryam
    Advisor
    Krishnan, Krishna K.
    Metadata
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    Abstract
    Supply chain companies are eager for an automated system to address their challenges, particularly those that are dynamic, such as dynamic vehicle routing problems. To prepare dynamic supply chain systems for organizations, Industry 4.0 must be applied. Despite ample studies that consider the Dynamic Vehicle Routing Problem (DVRP), the interactions between Industry 4.0 and DVRP have been rarely studied. Extensive reviews of current literature on supply chain networks, dynamic vehicle routing problems, and Industry 4.0 have recognized an urgent need to develop and understand the concept of Industry 4.0 and proposed to apply it in dynamic vehicle routing problems. Thus, this research addresses four imperative needs that have been structured into four research thrusts: 1) Industry 4.0 in logistics and supply chain management is presented through a systematic review and synthesis of the current literature on Industry 4.0 in Supply chain management. The goal here is to summarize the existing knowledge on Industry 4.0 in SCM, and to analyze the content of research papers using topic modeling (TM) techniques. 2) A two-stage metaheuristic algorithm for the dynamic vehicle routing problem: is used to develop a heuristic approach to dynamic vehicle routing problems with Industry 4.0 approach. 3) A Three-Stage algorithm for the Large Scale DVRP with an Industry 4.0 approach is employed to solve the DVRP on a large-scale size problem. 4) A Two-Stage algorithm for the Dynamic Multi-Depot Vehicle Routing Problem (DMDVRP) with an Industry 4.0 approach is utilized to solve the DMDVRP with respect to transportation cost. Overall, this dissertation's accomplishment is that Industry 4.0 plays a significant impact on supply chain and DVRP. The new proposed DVRP methodologies and corresponding results demonstrate that an acceptable cost-effective outcome is achievable.
    Description
    Thesis (Ph.D.)-- Wichita State University, College of Engineering, Dept. of Industrial, Systems and Manufacturing Engineering
    URI
    https://soar.wichita.edu/handle/10057/22485
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