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JAOT

Aerospace Mission Planning

Optimize satellite scheduling, mission planning, and component assembly sequencing. Aerospace operations involve coordinating communication windows, ground station coverage, and payload resources under tight time constraints -- problems where even small scheduling improvements yield significant operational gains.

When to Use This Guide

Use this guide for aerospace scheduling and resource allocation problems:

  • Satellite communication scheduling -- assign communication windows to satellites and ground stations to maximize data throughput
  • Launch window optimization -- select optimal launch times considering orbital mechanics, weather, and payload readiness
  • Assembly line sequencing -- order component assembly tasks to minimize total production time (makespan) for spacecraft or aircraft
  • Ground station allocation -- distribute satellite contacts across a network of ground stations to ensure coverage continuity

Step-by-Step Walkthrough

  1. Define your tasks or windows. For each communication window, record the satellite, eligible ground stations, time window (start/end), and data volume.

  2. Set resource constraints. Each ground station can handle at most one satellite contact at a time. Minimum handoff time between contacts must be respected.

  3. Add coverage requirements. Each satellite may need a minimum number of contacts per orbit or per day for health monitoring and data downlink.

  4. Choose your objective. Maximize total data downloaded, maximize coverage (number of successful contacts), or minimize the longest gap between contacts for any satellite.

  5. Run and interpret. The solver returns a contact schedule assigning each window to a ground station and time slot. Verify handoff gaps and antenna slew times are feasible.

Example: Satellite Ground Station Scheduling

Schedule 8 satellite communication windows across 4 ground stations over a 24-hour period. Each window has a duration, data volume, and set of eligible stations. Stations need at least 30 minutes between contacts for antenna repositioning.

import httpx

API_URL = "https://jaot.io/api/v2"
headers = {"Authorization": "Bearer ok_live_your_key_here"}

windows = {
    "W1": {"satellite": "SAT_A", "start": 0, "end": 4, "data": 120, "stations": ["GS1", "GS2"]},
    "W2": {"satellite": "SAT_A", "start": 8, "end": 12, "data": 150, "stations": ["GS2", "GS3"]},
    "W3": {"satellite": "SAT_B", "start": 2, "end": 6, "data": 100, "stations": ["GS1", "GS4"]},
    "W4": {"satellite": "SAT_B", "start": 14, "end": 18, "data": 130, "stations": ["GS3", "GS4"]},
    "W5": {"satellite": "SAT_C", "start": 1, "end": 5, "data": 110, "stations": ["GS1", "GS2"]},
    "W6": {"satellite": "SAT_C", "start": 10, "end": 14, "data": 140, "stations": ["GS2", "GS3"]},
    "W7": {"satellite": "SAT_D", "start": 6, "end": 10, "data": 160, "stations": ["GS3", "GS4"]},
    "W8": {"satellite": "SAT_D", "start": 18, "end": 22, "data": 170, "stations": ["GS1", "GS4"]},
}

stations = ["GS1", "GS2", "GS3", "GS4"]
handoff_gap = 0.5  # 30 min = 0.5 hours

# Binary: assign window w to station s
variables = [
    {"name": f"{w}_{s}", "type": "binary"}
    for w in windows
    for s in windows[w]["stations"]
]

# Maximize total data downloaded
objective = {
    "sense": "maximize",
    "coefficients": {
        f"{w}_{s}": windows[w]['data']
        for w in windows
        for s in windows[w]["stations"]
    },
}

constraints = []

# Each window assigned to at most one station
for w in windows:
    constraints.append({
        "name": f"assign_{w}",
        "coefficients": {
            f"{w}_{s}": 1 for s in windows[w]['stations']
        },
        "sense": "<=",
        "rhs": 1,
    })

# No two overlapping windows on the same station
# (check all pairs of windows sharing a station with overlapping times)
for s in stations:
    eligible = [w for w in windows if s in windows[w]["stations"]]
    for i in range(len(eligible)):
        for j in range(i + 1, len(eligible)):
            w1, w2 = eligible[i], eligible[j]
            # Check if time windows overlap (including handoff gap)
            if windows[w1]["end"] + handoff_gap > windows[w2]["start"] and \
               windows[w2]["end"] + handoff_gap > windows[w1]["start"]:
                constraints.append({
                    "name": f"conflict_{w1}_{w2}_{s}",
                    "coefficients": {f"{w1}_{s}": 1, f"{w2}_{s}": 1},
                    "sense": "<=",
                    "rhs": 1,
                })

response = httpx.post(f"{API_URL}/solve", headers=headers, json={
    "variables": variables,
    "objective": objective,
    "constraints": constraints,
})
result = response.json()

print(f"Status: {result['status']}")
print(f"Total data downloaded: {result['objective_value']:.0f} MB")
for w in windows:
    for s in windows[w]["stations"]:
        if result['solution'].get(f"{w}_{s}", 0) > 0.5:
            print(f"  {w} ({windows[w]['satellite']}) -> {s} "
                  f"[{windows[w]['start']}h-{windows[w]['end']}h, {windows[w]['data']}MB]")

The solver maximizes total data throughput by assigning each communication window to the best available ground station while respecting handoff gaps and antenna conflicts.

  • Custom Optimization -- build a fully custom mission scheduling model with time windows, precedence, and resource constraints

Next Steps