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Optimizing inbound freight mode decisions
(Massachusetts Institute of Technology, 2020)
Retail manufacturers often expedite inbound freight shipments from contract manufacturing bases to their distribution centers in destination markets at high cost to improve service levels to their wholesale partners and ...
Data-driven decision making in online and offline retail/
(Massachusetts Institute of Technology, 2020)
.Retail operations have experienced a transformational change in the past decade with the advent and adoption of data-driven approaches to drive decision making. Granular data collection has enabled firms to make personalized ...
Leveraging machine learning to solve The vehicle Routing Problem with Time Windows
(Massachusetts Institute of Technology, 2020)
The Vehicle Routing Problem with Time Windows (VRPTW) has been widely studied in the Operations Research (OR) literature given its increasingly widespread applications, ranging from school bus scheduling to packages delivery. ...
Dynamic optimization in the age of big data
(Massachusetts Institute of Technology, 2020)
This thesis revisits a fundamental class of dynamic optimization problems introduced by Dantzig (1955). These decision problems remain widely studied in many applications domains (e.g., inventory management, finance, energy ...
Investigations in applied probability and high-dimensional statistics
(Massachusetts Institute of Technology, 2020)
This thesis makes contributions to the areas of applied probability and high-dimensional statistics. We introduce the Attracting Random Walks model, which is a Markov chain model on a graph. In the Attracting Random Walks ...
Interpretable machine learning methods with applications to health care
(Massachusetts Institute of Technology, 2020)
With data becoming increasingly available in recent years, black-box algorithms like boosting methods or neural networks play more important roles in the real world. However, interpretability is a severe need for several ...
Online and offline learning in operations
(Massachusetts Institute of Technology, 2020)
With the rapid advancement of information technology and accelerated development of data science, the importance of integrating data into decision-making has never been stronger. In this thesis, we propose data-driven ...
Improving farmers' and consumers' welfare in agricultural supply chains via data-driven analytics and modeling : from theory to practice
(Massachusetts Institute of Technology, 2020)
The upstream parts of the agricultural supply chain consists of millions of smallholder farmers who continue to suffer from extreme poverty. The first stream of research in this thesis focuses on online agri-platforms which ...
Probabilistic models and optimization algorithms for large-scale transportation problems
(Massachusetts Institute of Technology, 2020)
This thesis tackles two major challenges of urban transportation optimization problems: (i) high-dimensionality and (ii) uncertainty in both demand and supply. These challenges are addressed from both modeling and algorithm ...
Optimization for online platforms
(Massachusetts Institute of Technology, 2021)
In the last decade, there has been a surge in online platforms for providing a wide variety of services. These platforms face an array of challenges that can be mitigated with appropriate modeling and the use of optimization ...