2021 IEEE/ACS 18th International Conference on Computer Systems and Applications (AICCSA) 2021
DOI: 10.1109/aiccsa53542.2021.9686909
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An Exact Algorithm for A Multi-Period Inventory Routing Problem with Lateral Transshipment

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Cited by 4 publications
(3 citation statements)
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“…A comparison between the results obtained in the IRPTW case and the VRP with time windows (VRPTW) was made by the researchers which showed that when the solution of the total distribution cost over the whole-time horizon generated higher costs than the IRPTW. Amri-Sakhri et al treated the case of a deterministic replenishment demand in a distribution network consisting of a supplier and a set of customers to be served by a single vehicle over the planning horizon [39]. They used the model as the basis for building their models [6].…”
Section: Zapata-cortes Et Al Proposed An Inventory Routing Problemmentioning
confidence: 99%
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“…A comparison between the results obtained in the IRPTW case and the VRP with time windows (VRPTW) was made by the researchers which showed that when the solution of the total distribution cost over the whole-time horizon generated higher costs than the IRPTW. Amri-Sakhri et al treated the case of a deterministic replenishment demand in a distribution network consisting of a supplier and a set of customers to be served by a single vehicle over the planning horizon [39]. They used the model as the basis for building their models [6].…”
Section: Zapata-cortes Et Al Proposed An Inventory Routing Problemmentioning
confidence: 99%
“…Problem Type Coelho et al [25] IRPT Coelho and Laporte [26] MIRPT with Homogeneous and Heterogeneous fleets and Consistency constraints Coelho and Laporte [27] IRP under OTL policy Adulyasak et al [28] MIRP and MPRP Chrysochoou and Zil-iaskopoulos [29] SIRPT Archetti et al [30] IRP under RMI and VMI Cheng et al [32] G-HIRP Schenekemberg et al [33] 2E-IRP and 2E-PRP Zapata-Cortes et al [35] IRPTW Amri-Sakhri et al [39] IRP with variable lead time and IRPLT In the following, we present studies conducted in different IRP models using in the computational tests the benchmarks of [6].…”
Section: Referencementioning
confidence: 99%
“…• Product quantity 𝑟𝑟 𝑖𝑖 consumed by customer i and randomly generated as an integer number in the interval [10,100];…”
Section: Implementation and Benchmarksmentioning
confidence: 99%