Selected work / Capstone
Route Flow Optimizer
A capstone chemical-delivery planning platform designed to turn complex operational inputs into clearer route-planning workflows.
- Status
- Capstone project · case study in progress
- Role
- Team lead, Spring 2026
- Stack
- Next.js · FastAPI · OR-Tools · Azure PostgreSQL
Overview
Route Flow Optimizer brings operational data, constrained route optimization, and dispatcher-facing workflows into a single chemical-delivery planning platform.
This case study documents the supported project context now and leaves clearly structured room for verified detail as the work is prepared for public review.
Operational problem
Chemical-delivery planning is information-heavy and constraint-driven. The project focuses on replacing fragmented, manual planning work with a clearer software workflow.
My role
I led the capstone team in Spring 2026. My work included helping define the project, guiding implementation, and keeping the system connected to the practical workflow it was meant to support.
Stakeholders and users
The platform is organized around dispatcher-facing planning workflows. More specific stakeholder and research detail will be added only after it is cleared for public sharing.
System overview
The current stack separates the Next.js interface, FastAPI application services, OR-Tools optimization work, and Azure PostgreSQL persistence.
- Next.js — dispatcher-facing interface
- FastAPI — application services
- OR-Tools — constrained route optimization
- Azure PostgreSQL — operational data persistence
Technical decisions
The architecture keeps the planning interface, service layer, optimization engine, and data store distinct. Detailed decision records are still being prepared and will be added with supporting context.
Challenges and tradeoffs
Constraint-heavy operational tools have to balance optimization behavior with workflows that people can understand and use. Verified examples and tradeoff notes are still to be added.
Outcome
The capstone produced a planning platform and a maintainable technical foundation. Public outcome details and any measurable results are intentionally omitted until they can be verified and shared responsibly.
Lessons learned
A fuller reflection on team leadership, system design, and working with an operational problem is in progress.
Screenshot and diagram gallery
These slots are ready for reviewed project media. They are intentionally labeled instead of using fabricated screens.