Publications

Using Deep Neural Networks for Scheduling Resource-Constrained Activity Sequences. PhD dissertation
Pagani, P.
2022, October 17. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000151132

EU DEMO Remote Maintenance System development during the Pre-Concept Design Phase
Crofts, O.; Loving, A.; Torrance, M.; Budden, S.; Drumm, B.; Tremethick, T.; Chauvin, D.; Siuko, M.; Brace, W.; Milushev, V.; Mittwollen, M.; Lehmann, T.; Rauscher, F.; Fischer, G.; Pagani, P.; Wang, Y.; Baars, C.; Vale, A.
2022. Fusion Engineering and Design, 179, Art.-Nr. 113121. doi:10.1016/j.fusengdes.2022.113121

Deep neural networks for the scheduling of resource-constrained activity sequences: A preliminary investigation [Tiefe neuronale netze für die planung von ressourcenbeschränkten aktivitäts-folgen: Eine vorläufige untersuchung]
Pagani, P.; Pfann, F.
2020. Logistics Journal, 2020. doi:10.2195/lj_Proc_pagani_en_202012_01

A digital twin concept for the development of a DEMO maintenance logistics modelling tool
Rauscher, F.; Fischer, G.; Lehmann, T.; Zapata, J. J.; Pagani, P.; Loving, A.
2021. Fusion Engineering and Design, 168, Art.-Nr.: 112399. doi:10.1016/j.fusengdes.2021.112399

The remote handling system of IFMIF-DONES
Miccichè, G.; Ascott, M.; Bakic, A.; Bernardi, D.; Brenosa, J.; Coloma, S.; Crofts, O.; Di Gironimo, G.; Ferre, M.; Fischer, G.; Ibarra, A.; Karap, A.; Kiss, I. G.; Kunert, C.; Lorenzelli, L.; Mitchell, G.; Mittwollen, M.; Pagani, P.; Papa, S.; Porempovics, G.; Tadic, T.; Matyas, T.
2019. Fusion engineering and design, 146, 2786–2790. doi:10.1016/j.fusengdes.2019.01.112

A logistical simulation tool to quantitatively evaluate the effect of different maintenance solutions on the total maintenance downtime for fusion reactors
Pagani, P.; Fischer, G.; Farquhar, I.; Skilton, R.; Mittwollen, M.
2019. Fusion engineering and design, 141, 121–124. doi:10.1016/j.fusengdes.2019.02.085

Maintenance logistics for IFMIF-DONES
Mittwollen, M.; Fischer, G.; Pagani, P.; Kunert, C.; Oellerich, J.; Lehmann, T.; Micciche, G.; Ibarra, A.
2019. Fusion engineering and design, 146 (B), 2743–2747. doi:10.1016/j.fusengdes.2019.05.017

A neural network-based algorithm with genetic training for a combined job and energy management for AGVs : Auftragsvergabe und energieverwaltung basierend auf mit genetischen algorith-men trainierten neuronalen netzen für fahrerlose transportsysteme
Pagani, P.; Colling, D.; Furmans, K.
2018. Logistics journal / Referierte Veröffentlichungen, 2018. doi:10.2195/lj_Proc_pagani_en_201811_01

Neural network-based genetic job assignment for automated guided vehicles = Auftragsvergabe basierend auf mit genetischen algorithmen trainierten neuronalen netzen für fahrerlose transportsysteme
Pagani, P.; Colling, D.; Furmans, K.
2017. Logistics journal / Referierte Veröffentlichungen, 2017. doi:10.2195/lj_Proc_pagani_en_201710_01

Performance evaluation of closed-loop logistics systems with generally distributed service times
Epp, M.; Pagani, P.; Stoll, J.; Scherer, S.; Rohlehr, C.; Furmans, K.
2017. Proceedings of the Second KSS Research Workshop : Karlsruhe, Germany, February 2016. Ed.: P. Hottum, 120–130, Karlsruher Institut für Technologie (KIT)

Performance evaluation of closed-loop logistics systems with generally distributed service times
Epp, M.; Pagani, P.; Stoll, J.; Scherer, S.; Rohlehr, C.; Furmans, K.
2016. Proceedings of the Karlsruhe Service Summit Research Workshop 2016, KSS 2016, Karlsruhe, 25.-26. Februar 2016

An Exact Model to Determine the Lead-Time Distribution of Perishable Goods in a Kanban-Controlled Production System = [Ein exaktes modell zur bestimmung der durchlaufzeitverteilung von umge-bungsempfindlichen gütern in einem kanban-gesteuerten produktionssystem]
Pagani, P.; Epp, M.; Furmans, K.
2016. Logistics journal / Referierte Veröffentlichungen, 2016 (10). doi:10.2195/lj_Proc_pagani_en_201610_01

An analytical method to calculate the cycle time distribution of closed queueing systems with arbitrary topology and generally distributed service times. Working Paper
Epp, M.; Pagani, P.; Rohlehr, C.; Furmans, K.
2015. Karlsruher Institut für Technologie (KIT)

A decomposition approach for the calculation of the cycle time distribution of closed queueing systems
Epp, M.; Stoll, J.; Scherer, S.; Pagani, P.; Furmans, K.
2015. 10th Conference on Stochastic Models of Manufacturing and Service Operations, June 1-6, 2015, Volos, Greece, 59–66, University of Thessaly Press