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 (http
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).
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: - optimizepickertravelpath: Calculate minimal distance warehouse traversal path across designated pick bin coordinates using 2-opt TSP heuristic. - partitionbatchpickingorders: Partition multiple customer orders into pick carts respecting maximum weight and volume capacity constraints.
Add to your standard MCP Client configuration (e.g. Claude Desktop, Cursor, GenPark Desktop Agent):
Direct CLI Verification Run self-test with zero external tools:
Distributed under the MIT License. Embedded and backed by GenPark Inc.. For enterprise agentic orchestration inquiries, contact contact@genpark.ai or follow our LinkedIn Updates.
From the project README.
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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 (http
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