Intelligent Aircraft Scheduling Engine Development

Overview
We're developing an intelligent aircraft scheduling engine to optimize light aircraft operations for non scheduled airlines Your task will be to implement the Phase 1 optimization engine: a single-day, JSON-driven scheduler that assigns aircraft and passengers to minimize operational cost with efficient routing selection.

You’ll be working alongside our C#/Blazor frontend team and integrating your work into an Azure-hosted SaaS platform via REST API.

Core Responsibilities
Build a solver in Python using Google OR-Tools to handle:

Passenger booking allocation across multiple aircraft

Aircraft routing based on fuel burn, turnaround time, airport performance limits

Weight and time window constraints

Implement a metaheuristic solution (not exact MIP) targeting runtime under 45 seconds

Respect the provided JSON input/output schema and constraints

Handle multiple booking types (passengers, staff, freight) with phase-based allocation

Produce clean and testable code, ideally as an Azure Function (optional for now)

Technical Environment
Solver platform: Python + Google OR-Tools

Input/output: Strict JSON schema – provided

Architecture: RESTful microservices (you deliver JSON-only component)

DB: MS SQL Server (mapped externally by our team)

DevOps: Azure Functions , GitHub

Deliverables
A functioning Python module that takes a JSON input and returns an optimized schedule

Support for:

Multi-aircraft routing

Seat and weight constraints

Fuel limits and turnaround times

Phase separation:

Phase A: Passenger allocation

Phase B: Staff allocation to remaining capacity (lower priority)

Sample test run on provided input dataset

What You’ll Be Given
JSON schema (input/output v11)

Sample input file (passengers, airports, aircraft, matrix data)

Visual UI references (Blazor mockups)

Developer briefing PDF with database mappings and business context

Required Experience
Proven track record with Google OR-Tools (VRP, CVRP, time windows, local search) and experience in solving heuristic NP-Hard problems.

Strong Python skills

Familiarity with aviation routing or logistics preferred

Experience handling constraints like weight, time windows, and fleet heterogeneity

JSON schema compliance and clean data validation

GitHub or similar for code delivery

How to Apply
Please provide:

A short summary of your relevant experience

A GitHub repo or sample project solving a VRP-style problem

Optional: Estimated timeline to deliver a working MVP

Whether you can test against our provided JSON file in the first round

Optional Message to Include
If you're confident with OR-Tools but would prefer an alternate solver (e.g., Gurobi, CPLEX), feel free to suggest your approach but we require a benchmark implementation using OR-Tools and JSON to compare.