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Explore partial centralization in durable-good supply chains, analyzing equilibrium outcomes and optimal ownership levels based on product durability and decision horizons.
Explore a data-driven matching algorithm for ride pooling, leveraging rank aggregation and machine learning to optimize driver-rider pairings using real-world data from a startup.
Explore limitations of Elo ratings in real-world games. Discover a new disc ranking system with skill and consistency scores. Examine empirical validation on bot and human game data.
Explore an alternative dynamic theory of coalition breakdown, examining endogenous exit problems and characterizing solutions in a linear-quadratic frame with time-invariant sharing rules.
Explore deep learning applications in power systems, focusing on Graph Neural Networks to address topological changes and optimize grid operations through unsupervised learning.
Explore data-driven decision-making through distributionally robust optimization, focusing on computation, statistics, and real-time implementation aspects. Gain insights into online optimization applications.
Explore open-loop Nash equilibria in games with time-varying delays, focusing on sufficient optimality conditions and applications to active vehicle suspension systems.
Explore a tree-search heuristic for stochastic production-distribution planning, optimizing costs and lead times across transportation modes. Gain insights into efficient problem-solving techniques for complex supply chain scenarios.
Explore Neo-Bayesian Statistics foundations, examining alternative probability theories and their implications for statistical inference, dynamic consistency, and capacity updating.
Explore key concepts in decision-making under uncertainty, including Expected Utility and Maxmin EU. Discover applications in robust statistics, fuzzy systems, climate change, and finance.
Explore economic growth with renewable environmental goods, analyzing sustainability problems and the Green Golden Rule concept through dynamic game theory and optimal control.
Explore demand information acquisition strategies in dual-channel supply chains, examining impacts on retailers, manufacturers, customers, and society.
Explore innovative neural PDE solver for accurate, scalable climate predictions. Learn about mesh-agnostic architecture combining Implicit Neural Representations and Graph Neural Networks.
Explore distributionally robust risk-averse network interdiction, focusing on randomized strategies' effectiveness in extreme loss scenarios. Gain insights into optimization techniques and numerical experiments.
Explore Stackelberg competition in groundwater resource management, focusing on irrigation and priority extraction for new uses. Analyze open-loop and feedback equilibrium strategies.
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