📍🚚 IVCP Route Optimizer 🗺️📍

Iterative Value-Centric Perturbation: A High-Performance TSP JavaScript Engine for Edge Devices

1. Overview & Repository Contents

The IVCP Route Optimizer is a novel heuristic engine designed to solve the Traveling Salesperson Problem (TSP) under priority-based constraints. Unlike standard solvers that treat every stop equally, IVCP utilizes a Value-Centric approach to ensure the most critical asset is handled first, followed by a deterministic refinement process to minimize total distance.

• 📝 Technical Note - IVCP Route Optimizer - Google Docs.pdf: The full technical note detailing the value-centric heuristic architecture, the deterministic 2-Opt refinement phases, and the 13.26% efficiency benchmark constraints.
• 📱 ivcp_engine.js: The core production engine written as a zero-dependency ES6 module, handling the complete local optimization pipeline from value-driven initialization to Hamiltonian cycle refinement.
• ⚙️ IVCP_Route_Optimizer_Testbench.html: A standalone browser-based environment used to benchmark routing efficiency across variable node densities ($5 \le N \le 50$).

2. Key Commercial Advantages

• Offline-Ready (Edge First): Designed for local execution on handheld devices, scanners, and IoT hardware. No internet connection or costly API calls to Google/Mapbox are required for the optimization.
• Significant Efficiency Gains: Benchmarked at a 13.26% Net Efficiency Gain over standard greedy dispatchers in high-variance environments.
• Operational Priority: Guaranteed initiation at the node with the highest priority value ($$\text{argmax}(V)$$), making it ideal for express deliveries or high-value logistics.

3. Technical Architecture

The engine employs a two-phase execution model:

• Phase 1: Value-Driven Initialization: Establishes a Hamiltonian cycle starting from the highest-value anchor using a nearest-neighbor approach.
• Phase 2: Deterministic 2-Opt Refinement: A greedy loop that performs segment reversals to "untangle" the route until a local optimum is reached.

4. Quick Start (Example Integration)

The engine is a zero-dependency ES6 module, making it lightweight and easy to integrate into existing logistics stacks.

import { IVCPOptimizer } from './sw/ivcp_engine.js';

const optimizer = new IVCPOptimizer();

// Data can be fetched from a local GPS/Database
const stops = [
    { id: "Order_101", x: 40.71, y: -74.00, value: 10 },
    { id: "Order_102", x: 40.75, y: -73.98, value: 5 }
];

const initial = optimizer.createInitialRoute(stops);
const finalRoute = optimizer.optimize(initial);

console.log("Optimized Sequence:", finalRoute.map(s => s.id));

5. Performance Benchmarks

Tested over 100 iterations with variable node density ($5 \le N \le 50$):

• Average Efficiency Improvement: 13.26%.
• Target Hardware: Mobile handhelds, edge gateways, and low-power IoT devices.

⚖️ Licensing & Commercial Use ⚖️

The IVCP Route Optimizer is available under a dual-licensing model to balance community innovation with high-performance commerical route optimization needs.

• Open Source (AGPL-3.0): Ideal for public research, open-source infrastructure, and community-driven projects. This license requires that any derivative works or network-hosted versions of the engine remain open-source.
• Commercial Entities: Licensing is available for integration into proprietary edge devices and logistics applications.

For commercial licensing inquiries, please contact: Licensing Agent:

J.E. Randolph 📧 700josh.r@gmail.com

---

Copyright (c) 2026 Jonathan Alan Reed

ORCID: 0009-0008-7345-1407