@techreport{JohannsmannCraparoDiekenetal.2020, type = {Working Paper}, author = {Johannsmann, Leonie M. and Craparo, Emily M. and Dieken, Thor L. and F{\"u}genschuh, Armin and Seitner, Bj{\"o}rn O.}, title = {Stochastic mixed-integer programming for a spare parts inventory management problem}, editor = {F{\"u}genschuh, Armin}, issn = {2627-6100}, doi = {10.26127/BTUOpen-5080}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:co1-opus4-50802}, year = {2020}, abstract = {The German Armed Forces provide an operation contingent to support the North Atlantic Treaty Organization (NATO) Response Force (NRF). For this purpose, a „warehouse" containing accommodations, food supplies, medical supplies, and spare parts for the systems has to be available. Such a warehouse is restricted in weight, in order to be quickly movable in an upcoming deployment situation. It should be able to supply the NRF troops for a certain amount of time (e.g., one month) without re-supply from the outside. To ensure optimal use of such a restricted warehouse, we developed the computer program „The OPtimization of a Spare Parts Inventory" (TOPSPIN) to find an optimal mix of spare parts to restore a set of systems to functionality. Each system is composed of several parts, and it can only be used again in the mission if all broken parts are replaced. The failure rate of the individual parts follows a given random distribution, and during deployment it is expected to be higher than in the homeland. Due to the stochastic nature of the problem, we generate scenarios that simulate the actual failure of the parts. The backbone of TOPSPIN is a mixed-integer linear program that determines an optimal, scenario-robust mix of spare parts and is solved using standard state-of-the-art numerical solvers. Using input data provided by the Logistikzentrum, we analyze how many scenarios need to be generated in order to determine reliable solutions. Moreover, we analyze the composition of the warehouse over a variety of different weight restrictions, and we calculate the number of repairable systems as a function of this bound.}, subject = {Logisitcs; Scenario generation; Bestandsmanagement; Logistik; Ganzzahlige Optimierung; Stochastische Optimierung; Operations Research; Uncertainty; Warehouse management; Operations research; Two-stage stochastic optimization; Mixed-integer programming; Logistik; Szenario-Erzeugung; Unsicherheit; Lagermanagement; Gemischt-ganzzahlige Optimierung; Unternehmensforschung; Zweistufige stochastische Optimierung}, language = {en} }