Optimisation of Safety Stock and Reorder Points for Multi-Item Multi-Location Inventory Networks
(2026) In Bachelor’s Theses in Mathematical Sciences NUMK11 20261Centre for Mathematical Sciences
Mathematics (Faculty of Sciences)
- Abstract
- Spare parts inventory management in multi-echelon supply chains presents a significant optimisation challenge, particularly in the commercial vehicle aftermarket where partavailability directly aects vehicle uptime and customer retention.
This thesis develops and evaluates a Mixed-Integer Linear Programming (MILP) model for jointly optimising reorder points and order quantities across a three-echelon network consisting of a Central Distribution Centre (CDC), a Support Distribution Centre (SDC), and Dealers, for multiple items over a discrete planning horizon.
The model is formulated under two objective functions: minimisation of total backorder volume across all locations and periods, and minimisation of total supply chain cost... (More) - Spare parts inventory management in multi-echelon supply chains presents a significant optimisation challenge, particularly in the commercial vehicle aftermarket where partavailability directly aects vehicle uptime and customer retention.
This thesis develops and evaluates a Mixed-Integer Linear Programming (MILP) model for jointly optimising reorder points and order quantities across a three-echelon network consisting of a Central Distribution Centre (CDC), a Support Distribution Centre (SDC), and Dealers, for multiple items over a discrete planning horizon.
The model is formulated under two objective functions: minimisation of total backorder volume across all locations and periods, and minimisation of total supply chain cost comprising of backorder penalty costs, inventory holding costs, order-line costs, and cost of lost sales at dealer level. Both formulations are subject to operational constraints including rounding requirements, full-truckload volumetric capacity, order-line thresholds, and a historical inventory value cap. The model is implemented using the Gurobi Optimizer and solved on an academic problem instance involving two items, three locations, and five planning periods.
Limitations including deterministic demand and a single replenishment channel per location are acknowledged and directions for future work are identified. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/student-papers/record/9239871
- author
- Abellaneda, Lou Ann LU
- supervisor
- organization
- alternative title
- Optimering av säkerhetslager och beställningspunkter för lagernätverk med flera artiklar och flera platser
- course
- NUMK11 20261
- year
- 2026
- type
- M2 - Bachelor Degree
- subject
- publication/series
- Bachelor’s Theses in Mathematical Sciences
- report number
- LUNFNA-4072-2026
- ISSN
- 1654-6229
- other publication id
- 2026:K20
- language
- English
- id
- 9239871
- date added to LUP
- 2026-09-14 16:33:46
- date last changed
- 2026-09-14 16:33:46
@misc{9239871,
abstract = {{Spare parts inventory management in multi-echelon supply chains presents a significant optimisation challenge, particularly in the commercial vehicle aftermarket where partavailability directly aects vehicle uptime and customer retention.
This thesis develops and evaluates a Mixed-Integer Linear Programming (MILP) model for jointly optimising reorder points and order quantities across a three-echelon network consisting of a Central Distribution Centre (CDC), a Support Distribution Centre (SDC), and Dealers, for multiple items over a discrete planning horizon.
The model is formulated under two objective functions: minimisation of total backorder volume across all locations and periods, and minimisation of total supply chain cost comprising of backorder penalty costs, inventory holding costs, order-line costs, and cost of lost sales at dealer level. Both formulations are subject to operational constraints including rounding requirements, full-truckload volumetric capacity, order-line thresholds, and a historical inventory value cap. The model is implemented using the Gurobi Optimizer and solved on an academic problem instance involving two items, three locations, and five planning periods.
Limitations including deterministic demand and a single replenishment channel per location are acknowledged and directions for future work are identified.}},
author = {{Abellaneda, Lou Ann}},
issn = {{1654-6229}},
language = {{eng}},
note = {{Student Paper}},
series = {{Bachelor’s Theses in Mathematical Sciences}},
title = {{Optimisation of Safety Stock and Reorder Points for Multi-Item Multi-Location Inventory Networks}},
year = {{2026}},
}