TY  - JOUR
A1  - Brewka, Gerhard
A1  - Ellmauthaler, Stefan
A1  - Kern-Isberner, Gabriele
A1  - Obermeier, Philipp
A1  - Ostrowski, Max
A1  - Romero, Javier
A1  - Schaub, Torsten H.
A1  - Schieweck, Steffen
T1  - Advanced solving technology for dynamic and reactive applications
JF  - Künstliche Intelligenz
Y1  - 2018
U6  - https://doi.org/10.1007/s13218-018-0538-8
SN  - 0933-1875
SN  - 1610-1987
VL  - 32
IS  - 2-3
SP  - 199
EP  - 200
PB  - Springer
CY  - Heidelberg
ER  - 
TY  - JOUR
A1  - Gebser, Martin
A1  - Obermeier, Philipp
A1  - Schaub, Torsten H.
A1  - Ratsch-Heitmann, Michel
A1  - Runge, Mario
T1  - Routing driverless transport vehicles in car assembly with answer set programming
JF  - Theory and practice of logic programming
N2  - Automated storage and retrieval systems are principal components of modern production and warehouse facilities. In particular, automated guided vehicles nowadays substitute human-operated pallet trucks in transporting production materials between storage locations and assembly stations. While low-level control systems take care of navigating such driverless vehicles along programmed routes and avoid collisions even under unforeseen circumstances, in the common case of multiple vehicles sharing the same operation area, the problem remains how to set up routes such that a collection of transport tasks is accomplished most effectively. We address this prevalent problem in the context of car assembly at Mercedes-Benz Ludwigsfelde GmbH, a large-scale producer of commercial vehicles, where routes for automated guided vehicles used in the production process have traditionally been hand-coded by human engineers. Such adhoc methods may suffice as long as a running production process remains in place, while any change in the factory layout or production targets necessitates tedious manual reconfiguration, not to mention the missing portability between different production plants. Unlike this, we propose a declarative approach based on Answer Set Programming to optimize the routes taken by automated guided vehicles for accomplishing transport tasks. The advantages include a transparent and executable problem formalization, provable optimality of routes relative to objective criteria, as well as elaboration tolerance towards particular factory layouts and production targets. Moreover, we demonstrate that our approach is efficient enough to deal with the transport tasks evolving in realistic production processes at the car factory of Mercedes-Benz Ludwigsfelde GmbH.
KW  - automated guided vehicle routing
KW  - car assembly operations
KW  - answer set programming
Y1  - 2018
U6  - https://doi.org/10.1017/S1471068418000182
SN  - 1471-0684
SN  - 1475-3081
VL  - 18
IS  - 3-4
SP  - 520
EP  - 534
PB  - Cambridge Univ. Press
CY  - New York
ER  - 
TY  - JOUR
A1  - Gebser, Martin
A1  - Kaminski, Roland
A1  - Kaufmann, Benjamin
A1  - Lühne, Patrick
A1  - Obermeier, Philipp
A1  - Ostrowski, Max
A1  - Romero Davila, Javier
A1  - Schaub, Torsten H.
A1  - Schellhorn, Sebastian
A1  - Wanko, Philipp
T1  - The Potsdam Answer Set Solving Collection 5.0
JF  - Künstliche Intelligenz
N2  - The Potsdam answer set solving collection, or Potassco for short, bundles various tools implementing and/or applying answer set programming. The article at hand succeeds an earlier description of the Potassco project published in Gebser et al. (AI Commun 24(2):107-124, 2011). Hence, we concentrate in what follows on the major features of the most recent, fifth generation of the ASP system clingo and highlight some recent resulting application systems.
Y1  - 2018
U6  - https://doi.org/10.1007/s13218-018-0528-x
SN  - 0933-1875
SN  - 1610-1987
VL  - 32
IS  - 2-3
SP  - 181
EP  - 182
PB  - Springer
CY  - Heidelberg
ER  -