In this paper, we propose an efficient payment scheme for sustaining cooperation in finitely many times repeated Prisoner's Dilemma games. The scheme is pa...

We characterize cooperative and non-cooperative solutions of a dynamic game played over event tree when the transition probability are not given. We assume...

Operating mining complexes constantly collect data from a wide variety of sources that directly or indirectly measure pertinent geological and geometallurg...

We develop a maximum-likelihood (ML) approach based on option markets for estimating structural models. We use dynamic programming and finite elements, der...

As the need for interpretable machine learning continues to grow, we propose a novel post-clustering method to generate counterfactual explanations for clust...

Training language models (LMs) under tight GPU memory budgets rules out standard back-propagation and motivates zeroth-order (ZO) optimization. While ZO m...

We study the integration of multi-period assignment, routing, and scheduling of care workers for home health care services. In such a context, it is importa...

Many combinatorial optimization problems, such as vehicle and crew scheduling, can be modeled using path-flow formulations, where each variable represents a ...

One-dimensional models can enable the assessment of the dynamic behavior of hydropower units during transient operation with minimal computational resources....

This paper investigates a class of linear-quadratic-Gaussian risk-sensitive graphon mean-field games, involving an asymptotically infinite population of hete...

Two families of directional direct search methods have emerged in derivative-free and blackbox optimization (DFO and BBO), each based on distinct principles:...

The present work studies the problem of sorting using comparisons involving three elements at a time. Each comparison only identifies the smallest, middle, ...

In this work, we propose improved task mapping strategies for real-time electric power system simulations on heterogeneous computing clusters, considering bo...

In addressing climate change, countries rely on two primary strategies: mitigation, which aims to reduce greenhouse gas emissions, and adaptation, which seek...

Modern power distribution networks (DNs) increasingly incorporate active distribution network technologies, such as distributed energy resources (DERs) and r...

Surrogate modeling with insufficient data can lead to high prediction uncertainty and errors. A promising remedy to address this issue is the use of transfer...

This paper introduces a novel variant of the Production Routing Problem (PRP) in a Two-Echelon supply chain involving multiple production plants, distributio...

We introduce Spatial Pattern Regression (SPR), a method to generate gridded historical meteorological data for climate adaptation. SPR operates in two steps:...

Large-scale distributed wireless networks provide infrastructure-free and cost-effective connectivity, supporting applications from disaster recovery to glob...

Rolling stock scheduling and crew scheduling are two fundamental problems that arise in the planning of urban rail operations and that are especially importa...