Data-driven decision making under uncertainty using matrices
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Updated
Nov 15, 2024 - Julia
Data-driven decision making under uncertainty using matrices
An energy system optimization model that is flexible, computationally efficient, and academically robust.
Dantzig-Wolfe series of decomposition and reformulation algorithm to solve MILP
Automated Test Assembly with Julia
Capacitated clustering problem (CCP) solved using Gurobi and heuristic optimization like LP-and-fix and size reduction.
Solving the influence maximization problem with independent cascade diffusion model.
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