Essays on last mile logistics alliances and the finite horizon joint replenishment problem

The first and second essay in the thesis focus on analyzing and developing mechanisms for implementing collaboration between logistic service providers (LSPs) undertaking last-mile delivery of ecommerce parcels and to share cost savings generated through collaboration between the LSPs. These works...

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書目詳細資料
主要作者: Jagannathan, Madhav
其他作者: Viswanathan, S
格式: Thesis-Doctor of Philosophy
語言:English
出版: Nanyang Technological University 2023
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在線閱讀:https://hdl.handle.net/10356/165468
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機構: Nanyang Technological University
語言: English
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總結:The first and second essay in the thesis focus on analyzing and developing mechanisms for implementing collaboration between logistic service providers (LSPs) undertaking last-mile delivery of ecommerce parcels and to share cost savings generated through collaboration between the LSPs. These works were motivated by some industry workshops organized by Volvo and supported by Enterprise Singapore/Media Development Authority and insights garnered from practicing senior managers of logistics companies during the workshop. The primary questions these two pieces of work address are: 1) Broadly, what are the mechanisms for structuring the logistics alliances among last-mile delivery players to achieve greater system efficiency and reduce CO2 emissions? 2) How should a bidding/offering mechanism be designed to ensure the savings allocation based on cooperative mechanisms are achieved in an arms-length system of sharing delivery workload? One essay is on a stylized problem involving delivery between two points (in either direction) with the objective of minimizing empty backhauls. The other essay addresses the problem of deliveries to several customers in a delivery route. The third essay considers the finite horizon joint replenishment problem with deterministic, non-stationary demands. We have proposed a new class of heuristic for the problem. The proposed heuristic draws inspiration from infinite horizon version of the problem for grouping items that are ordered together frequently. Then we apply optimal Wagner Whitin based algorithm to solve the problem for this group and a constrained optimal algorithm for each of the remaining items. Results of a comprehensive computational study revealed that the proposed heuristic performs better than other heuristics in the literature in most instances