Hugdrigo / Operations Lab / DispatchForge
COMMAND OVERVIEW · SYNTHETIC DATA

Delivery operations, clarified.

Plan feasible fleet routes, monitor time-window performance and surface capacity gaps across a fictional city service area.

● Scenario ready

Dispatch network

Schematic grid coordinates, not geographic roads or real travel times

Optimized routes

Fleet dispatch summary

Available vehicles and modeled delivery performance

Planning signal

Route capacity utilization

Packages assigned against each vehicle's capacity

Operational priorities

Late stops and demand that cannot be assigned

ROUTE OPTIMIZATION LAB

Plan the next dispatch.

Adjust dispatch capacity and service constraints. Routes are rebuilt using deterministic insertion and local improvement.

Capacity constrained

Dispatch controls

All changes are local. They do not change the underlying delivery stops.

Plan comparison

Naive sequential allocation versus heuristic routing

Different methods can trade distance against time-window performance. A shorter route does not always mean better service.

Calculated delivery runs

Travel and service times use a simple Euclidean grid proxy

DELIVERY REGISTRY

Manage your delivery stops.

Edit synthetic demand, geographic grid points, service windows and priorities. Archived stops can always be restored.

Add a delivery stop

Coordinates range from 0 to 100 on a fictitious city grid.

All fields required. Times must be in a valid order.

Delivery registry

Synthetic stops with non-destructive archiving

Delivery stopPriorityPackagesService windowGrid pointActions
DELIVERY STRESS TESTING

Explore operating conditions.

Model demand surges, slow travel and extra fleet capacity. All outcomes use synthetic assumptions.

Four presets

Scenario presets

Switch conditions without modifying your saved standard settings.

Baseline versus scenario

Operational metrics under the selected settings

Uncertainty experiment

240 reproducible demand and traffic draws

Scenario network

Illustrative spatial view of calculated routes

METHODOLOGY & RESPONSIBLE USE

Understand every calculation.

Plain-language assumptions, algorithm limits, data handling, and instructions to interpret the outputs responsibly.

Routing logic

Transparent deterministic heuristic, not an exact optimizer

01
Validate active stops

Use only stops with valid package counts, synthetic coordinates and service windows.

02
Assign by constrained insertion

Choose the best feasible vehicle position with capacity constraints and a lateness-penalized score.

03
Improve route sequence

Use bounded 2-opt reversals on each vehicle route while preserving capacity.

04
Evaluate time windows

Travel at assumed speed, wait for opening times and count stops that arrive after closing.

05
Stress-test assumptions

Run 240 deterministic synthetic draws with modest demand and traffic variation. These are not calibrated confidence intervals.

Data integrity & limits

What this tool does and does not provide

Fictional map: Grid coordinates are arbitrary. Distance is straight-line Euclidean distance multiplied by a configurable constant, not road distance. Traffic, fuel, live GPS and actual vehicle routes are not retrieved.
Offline privacy: Input remains in this browser's local storage unless you export it. No backend, API keys, analytics, remote calls, or paid models are used.
Planning limitations: The heuristic may miss a globally optimal solution. Loading is represented by package count only. Driver shifts, holidays, legal hours, street restrictions and truck-specific routing are not modeled.
Operational rule: Never use this demo as a sole source for dispatching real vehicles. Validate locations, roads, schedules and real fleet constraints in a production-grade routing platform.

Calculation definitions

These simple equations are the source of the metrics.

Leg distance√(Δx² + Δy²) × 0.42Illustrative kilometer proxy
Vehicle utilizationAssigned ÷ CapacityAs a percentage per vehicle
Service complianceOn time ÷ ServedArrival at or before close

Routes depart at 08:00. Travel duration includes scenario slowdown. Service starts at the later of arrival and the opening time; arriving after closing is classified late. A return leg to the depot is included in distance. Maximum modeled stop count is 30, not a live production network.