Search our Publications
Results
Thiago Rios, Stefan Menzel, Bernhard Sendhoff, "Large Language and Text-to-3D Models for Engineering Design Optimization", arXiv, 2023.
AbstractThe current advances in generative AI for learning large neural network models with the capability to produce essays, images, music and even 3D assets from text prompts create opportunities for a manifold of disciplines. In the present paper, we study the potential of deep text-to-3D models in the engineering domain, with focus on the chances and challenges when integrating and interacting with 3D assets in computational simulation-based design o...
Download Bibtex file Per Mail Request
Johannes Varga, Emil Karlsson, Guenther Raidl, Elina Rönnberg, Fredrik Lindsten, Tobias Rodemann, "Speeding up Logic-Based Benders Decomposition by Strengthening Cuts with Graph Neural Networks", 9th International Conference on Machine Learning, Optimization, and Data Science (LOD), 2023.
AbstractLogic-based Benders decomposition is a technique to solve optimization problems to optimality. It works by splitting the problem into a master problem, which neglects some aspects of the problem, and a subproblem, which adds cuts to the master problem to account for those aspects. These cuts need to be refi ned to achieve good overall performance. In this paper we investigate the use of Machine Learning to learn a good refi nement procedure. We a...
Download Bibtex file Per Mail Request
Angus Kenny, Tapabrata Ray, Steffen Limmer, Hemant Singh, Tobias Rodemann, Markus Olhofer, "Hybridizing TPOT with Bayesian Optimization", GECCO 2023, pp. 502-510, 2023.
AbstractTree-based pipeline optimization tool (TPOT) is used to automatically construct and optimize machine learning pipelines for classification or regression tasks. The pipelines are represented as trees comprising multiple data transformation and machine learning operators — each using discrete hyper-parameter spaces — and optimized with genetic programming. During the evolution process, TPOT evaluates numerous pipelines which can be challenging ...
Download Bibtex file Download PDF
Muhammad Yousaf, Duane Detwiler, Fabian Duddeck, Stefan Menzel, Satchit Ramnath, Nate Zurbrugg, Mariusz Bujny, "Similarity-driven Topology Optimization for Statics and Crash via Energy Scaling Method", ASME Journal of Mechanical Design (JMD), 2023.
AbstractTopology Optimization (TO) is used in the initial design phase to optimize certain objective functions under given boundary conditions by finding suitable material distributions in a specified design domain. Currently available methods in industry work very efficiently to get topologically-optimized design concepts under static and dynamic load cases. However, conventional methods do not address the designer’s preferences about the final materi...
Download Bibtex file Download PDF
Hao Tong, Leandro Minku, Stefan Menzel, Bernhard Sendhoff, Xin Yao, "A Novel Optimization Framework for Dynamic Capacitated Arc Routing Problems", Genetic and Evolutionary Computation Conference Companion (GECCO Companion), 2023.
AbstractThe capacitated arc routing problem (CARP) aims at scheduling a fleet of vehicles with limited capacities to serve a set of tasks in a graph. The dynamic CARP (DCARP) optimization focuses on updating the vehicles’ service routes when unpredicted dynamic events happen and deteriorate the current service plan. Due to the outside vehicles are still being in their service when dynamic events happen and being located at different positions of the ...
Download Bibtex file Download PDF
Chao Wang, "Design for Collaborative Intelligence: From Connected Vehicle, Autonomous Driving, Robotics to AI ", University of Nottingham Ningbo China Science and Technology Open Day, 2023.
AbstractThe goal of the intelligent system should be to enhance human capabilities, not replace them. There is much more scope for humans and AI to complement each other than to compete, as their advantages lie in different aspects. This complementarity can be called Collaborative Intelligence (CI), which enables machines to achieve goals together with humans in complex environments. CI requires mutual understanding and seamless communication between the...
Download Bibtex file Per Mail Request
Steffen Limmer, "Bilevel Large Neighborhood Search for the Electric Autonomous Dial-a-Ride Problem", Transportation Research Interdisciplinary Perspectives, vol. 21, 2023.
AbstractThe electric autonomous dial-a-ride problem (E-ADARP) represents a challenging and practically relevant extension of the dial-a-ride problem, which takes electric vehicle charging into account. It introduces battery constraints and the option to recharge vehicles at different charging stations. The present paper proposes a bilevel large neighborhood search approach (BI-LNS) for the E-ADARP. In the outer level of the proposed approach, charging se...
Download Bibtex file Download PDF
Daniel Tanneberg and Michael Gienger, "Learning Type-Generalized Actions for Symbolic Planning", IEEE/RSJ International Conference on Intelligent Robots and Systems, 2023.
AbstractSymbolic planning is a powerful technique to solve complex tasks that require long sequences of actions and can equip an intelligent agent with complex behavior. The downside of this approach is the necessity for suitable symbolic representations describing the state of the environment as well as the actions that can change it. Traditionally such representations are carefully hand-designed by experts for distinct problem domains, which limits t...
Download Bibtex file Per Mail Request
Claudio Maffi and Jens Engel, "Evaluation and comparison of PV prediction quality of a sky imager", HRI-EU, 2023.
AbstractOn the premises of Honda R&D Germany in Offenbach, Main, a large photovoltaic (PV) system with a peak power of 750kW is installed. The PV system is connected to an energy management system (EMS), which manages how electric energy is distributed and stored in the building. In order to use efficiently the green energy provided by the PV system into the EMS, accurate predictions about the accessibile PV power are requested. Currently a meteorolo...
Download Bibtex file Per Mail Request
Chao Wang and Derck Chu, "Visualizing risk areas using augmented reality glasses as advanced driver-assistance system", AUTO UI 23, 2023.
AbstractIn complex driving scenarios, drivers often face the challenge of making quick decisions regarding the safety of crossing intersections or entering roundabouts. These decisions, prone to human error, can compromise road safety and driving efficiency. The recent advancements in augmented reality (AR) glasses hold significant potential for assisting drivers in avoiding such dangers. Unlike traditional AR heads-up displays (HUDs), AR glasses provide...
Download Bibtex file Download PDF
1 ... 3 4 5 6 7 8 ... 151
Follow us
