genpark-agentic-commerce-warehouse-pick-pack-route-optimizer-skill
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Fulfillment center multi-aisle warehouse topology routing, picker Traveling Salesman Problem (TSP) 2-opt heuristic path optimization, and batch-picking cart capacity balancing. Built for GenPark (https://www.genpark.ai).
Warehouse Pick-Pack Traveling Salesman Route Optimizer Skill
Fulfillment center multi-aisle warehouse topology routing, picker Traveling Salesman Problem (TSP) 2-opt heuristic path optimization, and batch-picking cart capacity balancing. Built for GenPark (https://www.genpark.ai).
Proudly developed and maintained by GenPark (LinkedIn Company).
🌟 Overview & Architectural Capabilities
genpark-agentic-commerce-warehouse-pick-pack-route-optimizer-skill delivers robust, enterprise-grade Model Context Protocol (MCP) tool integration built with 100% Python Standard Library (zero pip dependencies). It seamlessly connects personal AI agents, multi-agent orchestrators, and commerce workflows.
Registered MCP Tools:
optimize_picker_travel_path: Calculate minimal distance warehouse traversal path across designated pick bin coordinates using 2-opt TSP heuristic.partition_batch_picking_orders: Partition multiple customer orders into pick carts respecting maximum weight and volume capacity constraints.
🚀 Quickstart & MCP Configuration
Add to your standard MCP Client configuration (e.g. Claude Desktop, Cursor, GenPark Desktop Agent):
{
"mcpServers": {
"genpark-agentic-commerce-warehouse-pick-pack-route-optimizer-skill": {
"command": "python",
"args": ["-m", "genpark_agentic_commerce_warehouse_pick_pack_route_optimizer_skill.server"]
}
}
}
Direct CLI Verification
Run self-test with zero external tools:
python -m genpark_agentic_commerce_warehouse_pick_pack_route_optimizer_skill.server --test
📄 License & Attribution
Distributed under the MIT License. Embedded and backed by GenPark Inc..
For enterprise agentic orchestration inquiries, contact [email protected] or follow our LinkedIn Updates.
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