Hello Community members,
I hope someone can help me with this use case that I am trying to build.
Problem Statement:
I am building a logistics cost optimization model for a manufacturing company. The objective is to minimize the total per-unit cost of sourcing parts from multiple suppliers to multiple plants while considering complex shipment constraints.
Key Requirements:
Production Demand:
- Each plant has specific production volume requirements (e.g., 50,000 units for Memphis, 65,000 units for Detroit).
Supplier Selection:
- Parts can be sourced from multiple suppliers with varying capacities, distances, and transportation costs.
Shipment Capacity Constraints:
- Each truck has fixed cargo volume and weight limits (e.g., 2,000 parts per shipment).
- If demand exceeds truck capacity, additional shipments are required.
Cost Calculation:
- Per shipment cost: (Distance×Cost per Mile)
- Per-unit cost: (Total Shipment Cost+ Total Parts Cost)/Total Parts Delivered.
- Additional shipments increase the per-unit cost when demand exceeds the truck capacity and we will need additional truck.
Optimization Requirements:
- Minimize the total logistics cost by optimizing:
- Supplier selection
- Shipment allocation to meet plant demand at the lowest per-unit cost
- Constraints:
- Production demand must be fulfilled at each plant.
- Integer constraint for the number of shipments.
- Non-linear cost function due to additional shipments when capacity is exceeded.
Challenges Faced:
- Calculating per-unit costs dynamically when the number of shipments changes requires iterative computation.
Request for Assistance:
- How can I configure the Alteryx Optimization Tool to handle dynamic cost calculations?
- Are there alternative methods/tools to achieve this optimization in Alteryx?
