Spatial Optimization
Benders decomposition with two subproblem | Integer programming
locationallocation: an R package to solve Maximal Coverage Location-Allocation problems using geospatial data
Geo-Spatial Analytics using Location Allocation method
Using Genetic Algorithms to optimize the allocation of services or facilities to specific locations. The primary application of this project is in the context of Covid-19 vaccine center locations, aiming to strategically position vaccination facilities for efficient and widespread coverage.
A Unified ArcGIS Toolbox for Facility Location, Allocation, Service Area and Political Districting Problems
[WIP - alpha] A Python library for location optimization, focussing on solving methods that can output a range of solutions rather than just the 'best' option
Selects hypothetical polling place locations and voting precinct boundaries, given assumed voter residences, polling place facilities, street network, and area boundary. Uses Network Analyst in ArcGIS to solve Location-Allocation.
Spatial Optimization
Optimal placement of police cars to minimize response time to events in police districts.
Reproducibility package for a capacitated location-allocation model applied to religious small-group formation.
Python implementation of the optimization model proposed in paper titled "A mixed integer programming approach to improve oil spill response resource allocation in the Canadian arctic"
Fire station drive-time coverage and maximal covering location model for Brazos County, TX (OSMnx, 2020 Census, PuLP/HiGHS)
Optimized model with NSGA-II in Python, tuning hyperparameters via genetic algorithms for efficient real-world crisis mapping.
Data-driven optimization of shuttle stops, routes, and headways for the local festival
Explainable geospatial decision-support platform for Istanbul retail expansion: H3 microzones, network isochrones, Huff cannibalization, spatial CV demand forecasting, SHAP/AHP scoring, and budgeted maximum-coverage optimization.
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