Live Replanning

These two scenarios continue from a baseline plan created at 07:00 with two trucks serving nine jobs. By 11:00 the situation has changed and a replan is needed. See POST /optimize/replan for the full schema reference.

Baseline plan (07:00)

Two trucks started from depot (location index 0) at 07:00 (25,200 s) with a 10-location travel matrix and nine jobs spread across the day:

{
  "original_request": {
    "resources": [
      { "id": "truck_a", "start_location": {"index": 0}, "end_location": {"index": 0},
        "time_window": {"start": 25200, "end": 61200} },
      { "id": "truck_b", "start_location": {"index": 0}, "end_location": {"index": 0},
        "time_window": {"start": 25200, "end": 61200} }
    ],
    "jobs": [
      {"id": "job1", "location_index": 1, "service_time": 1800},
      {"id": "job2", "location_index": 2, "service_time": 1800},
      {"id": "job3", "location_index": 3, "service_time": 1800},
      {"id": "job4", "location_index": 4, "service_time": 1800, "time_windows": [{"start": 39600, "end": 43200}]},
      {"id": "job5", "location_index": 5, "service_time": 1800},
      {"id": "job6", "location_index": 6, "service_time": 1800},
      {"id": "job7", "location_index": 7, "service_time": 1800},
      {"id": "job8", "location_index": 8, "service_time": 1800, "time_windows": [{"start": 41400, "end": 46800}]},
      {"id": "job9", "location_index": 9, "service_time": 1800}
    ],
    "travel": {
      "time_matrix": [[0,600,900,780,1020,900,1140,1260,1320,1440],[600,0,480,540,780,900,960,1080,1200,1320],[900,480,0,300,600,780,840,960,1020,1200],[780,540,300,0,420,600,720,840,900,1080],[1020,780,600,420,0,360,540,720,780,960],[900,900,780,600,360,0,300,480,600,780],[1140,960,840,720,540,300,0,240,420,600],[1260,1080,960,840,720,480,240,0,240,420],[1320,1200,1020,900,780,600,420,240,0,240],[1440,1320,1200,1080,960,780,600,420,240,0]],
      "distance_matrix": [[0,6000,9000,7800,10200,9000,11400,12600,13200,14400],[6000,0,4800,5400,7800,9000,9600,10800,12000,13200],[9000,4800,0,3000,6000,7800,8400,9600,10200,12000],[7800,5400,3000,0,4200,6000,7200,8400,9000,10800],[10200,7800,6000,4200,0,3600,5400,7200,7800,9600],[9000,9000,7800,6000,3600,0,3000,4800,6000,7800],[11400,9600,8400,7200,5400,3000,0,2400,4200,6000],[12600,10800,9600,8400,7200,4800,2400,0,2400,4200],[13200,12000,10200,9000,7800,6000,4200,2400,0,2400],[14400,13200,12000,10800,9600,7800,6000,4200,2400,0]]
    },
    "options": {"time_limit_seconds": 10}
  }
}

Scenario: urgent job injection + cancellation (11:00)

Situation at 11:00 (39,600 s)

• job1, job2, job4 are completed.
• job3 has been cancelled by the customer — it must disappear from the plan without appearing in unserved.
• A new urgent job has arrived at location 8 with a hard time window 11:00–13:00 (39600–46800 s) and a high penalty.
• truck_a is at location 2 (its last completed stop), truck_b is at location 4.

Request

{
  "original_request": { "...same as baseline above..." },
  "completed_job_ids": ["job1", "job2", "job4"],
  "cancelled_job_ids": ["job3"],
  "vehicle_positions": [
    { "resource_id": "truck_a", "location_index": 2, "current_time": 39600 },
    { "resource_id": "truck_b", "location_index": 4, "current_time": 39600 }
  ],
  "new_jobs": [
    {
      "id": "job_urgent",
      "location_index": 8,
      "service_time": 1800,
      "time_windows": [{"start": 39600, "end": 46800}],
      "mandatory": true,
      "penalty": 500000
    }
  ]
}

What the solver does

• truck_a re-plans from location 2 at 11:00 (not the depot).
• truck_b re-plans from location 4 at 11:00.
• job3 is silently dropped — it will not appear in unserved.
• job_urgent has a hard window and a 500,000 penalty, giving the solver strong incentive to assign it first.
• truck_c (if present and not listed in vehicle_positions) retains its original depot start unchanged.

Scenario: all vehicles scattered, emergency job (14:00)

Situation at 14:00 (50,400 s)

All nine original jobs are done. All four trucks are scattered across the network. A new emergency job must be served within the next 60 minutes.

Request

{
  "original_request": { "...same baseline, but with 4 trucks..." },
  "completed_job_ids": [
    "job1", "job2", "job3", "job4", "job5",
    "job6", "job7", "job8", "job9"
  ],
  "cancelled_job_ids": [],
  "vehicle_positions": [
    { "resource_id": "truck_a", "location_index": 3,  "current_time": 50400 },
    { "resource_id": "truck_b", "location_index": 5,  "current_time": 50400 },
    { "resource_id": "truck_c", "location_index": 6,  "current_time": 50400 },
    { "resource_id": "truck_d", "location_index": 9,  "current_time": 50400 }
  ],
  "new_jobs": [
    {
      "id": "job_emergency",
      "location_index": 7,
      "service_time": 900,
      "time_windows": [{"start": 51000, "end": 54600}],
      "mandatory": true,
      "penalty": 1000000
    }
  ]
}

What the solver does

• All four trucks start from their current scattered positions, not the depot.
• The solver picks whichever truck can reach location 7 within the 14:10–15:10 window at minimum cost.
• Because all other jobs are complete, the only open work is the emergency job.
• Shift end (17:00, 61,200 s from the original request) is preserved automatically.