Rescheduling blocked Vehicles at Daimler AG
Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
The purpose of this thesis is to develop a heuristic solution for the static problem of resequencing unblocked vehicles as a part of an ongoing research project at Daimler AG. The target client of this project is Mercedes-Benz Cars.
An unblocked vehicle is defined as a vehicle that for some reason could not be processed in its given time slot but at a later point in time needs to be inserted into the production sequence. Work overload is defined as work that the worker is unable to finish prior to reaching the station border.
The resequencing problem can be described as finding new positions for a set of unblocked vehicles in a sequence of previously not blocked vehicles, such that the new sequence containing the previously not blocked vehicles and the additional unblocked vehicles causes as little work overload as possible. A decision has to be made in real-time, forcing the solution method to return a solution within a cycle time.
Today, Mercedes-Benz Cars uses the sequencing approach “car sequencing”. This approach relies on so called spacing constraints, which basically means, trying to distribute work intensive vehicles as evenly as possible over the planning horizon and thereby enabling a hopefully smooth production. The car sequencing approach needs limited information. The difficulty is to find spacing constraints that fits the high level of product customization characterizing a modern car manufacturer. To overcome these difficulties, a new approach is being considered, namely the mixed-model sequencing, which takes more detailed data into account than the car sequencing approach but on the other hand is more costly in terms of computation.
To this end, a simple but promising tabu search scheme was developed, that for many instances was able to find the optimal solution in less than 30 seconds of computing time and that also clearly outperformed all benchmark heuristics.
Place, publisher, year, edition, pages
2012. , 68 p.
Rescheduling mixed-model sequencing tabu search metaheuristic
Engineering and Technology
IdentifiersURN: urn:nbn:se:liu:diva-81455ISRN: LiU-ITN-TEK-A--12/052--SEOAI: oai:DiVA.org:liu-81455DiVA: diva2:552581
Subject / course
Master of Science in Communication and Transport Engineering
Engevall, Stefan, Tekn.Dr
Persson, Fredrik, Tekn.Dr