Print Email Facebook Twitter Optimisation methods for the multi-period petrol station replenishment problem Title Optimisation methods for the multi-period petrol station replenishment problem: A case study at AMCS Author Boers, Luke (TU Delft Civil Engineering and Geosciences; TU Delft Mechanical, Maritime and Materials Engineering) Contributor Brandt, Jelmer (mentor) Atasoy, Bilge (mentor) Homem de Almeida Correia, Gonçalo (graduation committee) Negenborn, Rudy (graduation committee) Degree granting institution Delft University of Technology Programme Transport, Infrastructure and Logistics Date 2020-01-07 Abstract The petrol distribution problem is well-known in the literature as the Petrol Station Replenishment Problem (PSRP). This research concerns a "rich" version of the multi-period PSRP with real-life characteristics, to represent the complexity of the practical problem. The planning is optimised over multiple days, since stations do not need to be replenished every day. Mixed-Integer Linear Programming (MILP) models and a decomposition heuristic are proposed as planning methods, which are evaluated with a case study based on a real-life petrol distributor. Variants to these MILP models are proposed for the situations where the inventory is allowed to drop below the safety stock level, where inventory levels need to be minimised and where the service time depends on the delivery quantity. Moreover, to determine delivery quantities, the heuristic uses the new introduced simultaneous dry run inventory policy. An improvement procedure is applied to improve the initial heuristic solution. A commercial solver is able to find solutions for instances with up to 20 stations and 7 days for the MILP models. Exact solutions are found for instances up to 10 stations and 5 days. A heuristic solution was found for the full case study of 59 stations and 14 days, within the time limit of two hours. Subject Petrol station replenishmentInventory routingSimultaneous dry runDecomposition heuristic To reference this document use: http://resolver.tudelft.nl/uuid:7a74bf32-342a-4b65-aa9c-718f19b194ba Part of collection Student theses Document type master thesis Rights © 2020 Luke Boers Files PDF Thesis_Luke_Boers.pdf 6.13 MB Close viewer /islandora/object/uuid:7a74bf32-342a-4b65-aa9c-718f19b194ba/datastream/OBJ/view