defense-logistics-optimizer

Name: Defense-Logistics-Optimizer
Author: Dryade

Tier: Enterprise | Type: Agent | Category: Defense | Version: 1.0.0

Defense supply chain and logistics optimization plugin with fuel consumption modeling, ammunition allocation planning, resupply route optimization, fleet readiness tracking, and supply chain bottleneck detection.

1. Overview

Plugin Name: defense-logistics-optimizer Slug: defense-logistics-optimizer Required Tier: Enterprise Plugin Type: Agent Category: Defense Author: Dryade License: DSUL

What It Does

Assists defense logistics officers with supply chain optimization by modeling fuel consumption rates per vehicle type and terrain, planning ammunition allocation per unit and intensity level, optimizing resupply routes with threat avoidance, tracking fleet readiness, and detecting supply chain bottlenecks.

Key Capabilities

Fuel consumption modeling by vehicle type (VAB, Leclerc, VLTT, etc.) and terrain
Ammunition allocation planning per unit type with intensity multipliers
Resupply route optimization with threat area avoidance
Fleet readiness tracking with maintenance scheduling
Supply chain bottleneck detection and mitigation

2. User Stories

Primary User Stories

US-1: Model Fuel Requirements

As a logistics officer, I want to model fuel consumption for a convoy so that I can ensure sufficient fuel is available for the operation.

Acceptance Criteria:

[ ] Fuel calculated per vehicle type with terrain multipliers
[ ] 20% reserve included in total
[ ] Results broken down per vehicle type

US-2: Detect Supply Chain Bottlenecks

As a supply chain manager, I want to identify bottlenecks in the logistics chain so that I can mitigate risks before they impact operations.

Acceptance Criteria:

[ ] Bottlenecks identified with severity rating
[ ] Impact description for each bottleneck
[ ] Mitigation recommendations provided

Edge Cases

Unknown vehicle type: Uses default 30L/100km consumption rate
Invalid distance: Falls back to 100km default

3. Architecture

Component Diagram

+------------------+     +---------------------+     +------------------+
|   Orchestrator   | --> |  Logistics Optimizer | --> |  Data Provider   |
|  Agent Tools     |     |  plugin.py           |     |  (mock / real)   |
+------------------+     +---------------------+     +------------------+
                                  |
                            +-----v------+
                            |  Demo Data |
                            |  data/*.json|
                            +------------+

Components

| Component | File | Responsibility | |-----------|------|----------------| | Plugin | plugin.py | Agent tools, mock/real toggle | | Data | data/ | Demo datasets (fuel rates, ammo, routes, fleet, supply chain) | | Tests | tests/test_plugin.py | Manifest, tools, data validation |

Dependencies

Internal: core.plugins.PluginProtocol, core.plugin_config_store.PluginConfigStore
External: None (air-gapped compatible)

4. API Spec / Agent Capabilities

Agent Tools

| Tool Name | Input | Output | Description | |-----------|-------|--------|-------------| | model_fuel_consumption | vehicle_types: str, distance_km: str, terrain: str | JSON fuel breakdown | Model fuel consumption per vehicle | | plan_ammunition_allocation | unit_type: str, operation_days: str, intensity: str | JSON allocation plan | Plan ammunition per unit | | optimize_resupply_route | origin: str, destination: str, threat_areas: str | JSON route recommendation | Optimize resupply routing | | assess_fleet_readiness | fleet_inventory: str | JSON readiness report | Assess fleet operational status | | detect_bottlenecks | supply_chain_description: str | JSON bottleneck analysis | Detect supply chain bottlenecks |

5. Data Flow

Processing Pipeline

1. User provides logistics parameters via orchestrator
2. Plugin loads consumption rates and inventory from data/ directory
3. Plugin calculates requirements with terrain/intensity multipliers
4. Audit trail appended to all outputs
5. JSON response returned to orchestrator

Demo Data Description

The data/ directory contains:

fuel-consumption-rates.json: Per-vehicle fuel rates with terrain multipliers
ammunition-tables.json: Per-unit ammunition allocation tables
resupply-routes.json: Route options with risk assessment and supply points
fleet-inventory.json: Vehicle fleet with operational/maintenance status
supply-chain.json: Supply chain nodes with bottleneck analysis

Total: 5 demo files covering logistics lifecycle.

6. Security Considerations

Data Handling

PII: No - synthetic military logistics data only
Encryption: N/A - all data local
Data Retention: No persistent storage beyond plugin config

External API Keys

None required. Designed for air-gapped deployment.

Isolation

Plugin runs in sandboxed context via core plugin loader
No external network calls
All demo data is unclassified (NP / EXERCICE)

7. Test Plan

Test Classes

| Class | Tests | Coverage Target | |-------|-------|----------------| | TestPluginAttributes | Manifest consistency | 100% manifest fields | | TestPluginConfig | Config, mock/real toggle | Config validation | | TestAgentTools | All 5 tools + terrain multiplier test | All tools | | TestDemoData | Data presence, loadability, classification | All data files |

Running Tests

cd dryade-plugins
python -m pytest enterprise/defense-logistics-optimizer/tests/ -x -v --tb=short

8. Deployment Notes

Requirements

No additional Python packages required.

Configuration

{
    "data_source": "mock"
}

Compatibility

Min Dryade Version: 1.0.0
Python: >=3.11
Notes: Designed for air-gapped deployment.

9. User Guide

Getting Started

Ensure your Dryade instance has an Enterprise tier license
Install the plugin via the marketplace or dryade-pm push
Ask the orchestrator to model fuel consumption or plan ammunition

Common Workflows

Workflow 1: Convoy Fuel Planning

Specify vehicle types and distance: "VAB, Leclerc, 200km cross-country"
Plugin models consumption with terrain multipliers and 20% reserve
Review total fuel requirements and resupply triggers

Workflow 2: Fleet Readiness Assessment

Request fleet readiness report
Plugin shows operational rates per vehicle type
Identifies vehicles with low readiness for maintenance priority

FAQ

Q: What vehicle types are supported in demo mode? A: VAB, Leclerc, VLTT, CAESAR, GBC_180, VBCI, AMX_10RC, PVP. Unknown types use a default rate.

10. Screenshots

Screenshots will be added after UI integration.

11. Changelog

1.0.0 (2026-03-05)

Initial release
Fuel consumption modeling with terrain multipliers
Ammunition allocation with intensity scaling
Resupply route optimization
Fleet readiness tracking
Supply chain bottleneck detection

Future Roadmap

[ ] Integration with defense-mission-planner for combined planning
[ ] Predictive maintenance scheduling based on usage patterns
[ ] Multi-depot optimization for complex supply chains

Defense-Logistics-Optimizer

Description

Screenshots

Details