This repository contains a functional AIMMS example for optimizing the placement and sizing of electric vehicle (EV) charging stations. It demonstrates how to solve a capacitated facility location problem (CFLP) within a geospatial context using metaheuristic optimization.
As EV adoption grows, urban planners face the challenge of building accessible and cost-effective infrastructure. This model helps address:
- Minimize Infrastructure Costs: Balancing construction and maintenance expenses.
- Reduce Range Anxiety: Positioning stations to ensure vehicles can reach them within their battery limits.
- Demand Fulfillment: Matching station capacity (number of chargers) with expected vehicle visit probabilities.
- Accessibility: Maximizing the reach of the charging network in continuous urban spaces.
To get the most out of this model, we highly recommend reading our detailed step-by-step guide on the AIMMS Community:
👉 Read the Full Article: EV Charging Location Guide
- AIMMS: You will need AIMMS installed to run the model. Download the Free Academic Edition here.
- WebUI: This application makes extensive use of the Map Widget and data-dependent CSS styling to visualize the "swarm" of potential solutions.
- Particle Swarm Optimization (PSO): Implements the Vulture algorithm to navigate non-linear, non-convex search spaces.
- Geospatial Optimization: Uses real-time adjustments of "particles" (stations) as they converge toward an optimal configuration.
- Capacity Constraints: Manages complex limits, such as a maximum of eight chargers per station and vehicle range decay functions.
- Download the Release: Go to the Releases page and download the
.zipfile. - Open the Project: Launch the
.aimmsfile. - Run the PSO: Use the WebUI workflow to initialize the problem and watch the algorithm iterate through generations on the map.
- Compare Scenarios: Adjust maintenance costs or vehicle ranges using sliders to see how the optimal layout shifts.
This example is maintained by the AIMMS User Support Team.
- Found an issue? Open an issue.
- Questions? Reach out via the AIMMS Community.
Maintained by the AIMMS User Support Team. We optimize the way you build optimization.