Torsten Reiners
Curtin University
134 Papers
643 Citations
Torsten Reiners is an academic researcher from Curtin University. The author has contributed to research in topics: Metaverse & Computer science. The author has an hindex of 19, co-authored 131 publications. Previous affiliations of Torsten Reiners include University of Hamburg & Auckland University of Technology.
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Papers
Design of a SWOT Analysis Model and its Evaluation in Diverse Digital Business Ecosystem Contexts
TL;DR: The research is designing a new SWOT model in which the elements are modelled to interrogate managers’ views to oversee new insights of a variety of business contexts that can guide SWOT analyzers and provide digital ecosystem services in multiple industry operations in an optimum manner.
188
Modeling and solving the short-term car rental logistics problem
Andreas Fink,Torsten Reiners +1 more
TL;DR: The results indicate that the proposed approach can significantly improve efficiency in the car rental business and under consideration of essential practical needs such as multi-period planning, a country-wide network, customized transportation relations, fleeting and defleeting, and car groups with partial substitutability.
126
Vehicle dispatching at seaport container terminals using evolutionary algorithms
J. Bose,Torsten Reiners,D. Steenken,S. Voss +3 more
- 01 Jan 2000
TL;DR: This work describes the main logistics processes in seaport container terminals and presents methods for their optimization, and investigates different dispatching strategies for straddle carriers to gantry cranes and shows the potential of evolutionary algorithms to improve the solutions.
111
Gamification in logistics and supply chain education: Extending active learning
Lincoln C. Wood,Torsten Reiners +1 more
- 01 Jan 2012
TL;DR: In this paper, the authors present a framework that combines several gamification elements that can be relatively easily incorporated into existing approaches and learning management systems (LMSs) in ways that aim to increase engagement and extend active learning.
76