Outline We present several optimization models and/or computational algorithms dealing with uncertain, dynamic/online, structured and/or massively distributed data:
Bridging prediction and decision: Advances and challenges in ...
Mar 18, 2025 · This review examines the transformative impact of big data and intelligent systems on traditional optimization paradigms, highlighting the continuum of data-driven optimization …
The robust optimization framework can incorporate a wide range of additional features, including ̄xed ordering costs, ̄xed lead times, integer order amounts, capacity on the orders and capacity …
Data-Driven Optimization: Enhancing Combinatorial ...
Apr 11, 2023 · This approach allows for the development of new solvers while leveraging the wealth of optimization theory and methods that have been developed over the years. …
Predict-and-Optimize Techniques for Data-Driven Optimization ...
Apr 12, 2025 · Throughout the paper, we aim to provide a valuable roadmap for researchers and practitioners in the field, guiding them to choose data-driven methods to solve their decision …
Explainable Data-Driven Optimization: From Context to ...
Jan 24, 2023 · We introduce two classes of explanations and develop methods to find nearest explanations of random forest and nearest-neighbor predictors. We demonstrate our approach …
Data-driven optimization algorithms - ScienceDirect
Jan 1, 2024 · Data-driven optimization emerged as an alternative to traditional optimization practices by developing efficient algorithms that use data to explore the best solution of a …