a5c-ai Network Optimization Modeler
Overview
The Network Optimization Modeler provides supply chain network design and optimization capabilities using mathematical modeling techniques. It supports facility location decisions, transportation lane optimization, inventory positioning, and cost-service tradeoff analysis.
Capabilities
- Center of Gravity Analysis: Geographic demand-weighted location analysis
- Mixed-Integer Linear Programming: Optimization model formulation and solving
- Facility Location Optimization: Warehouse and distribution center placement
- Transportation Lane Optimization: Freight lane and mode optimization
- Inventory Positioning by Node: Multi-echelon inventory placement
- Cost-Service Tradeoff Analysis: Pareto frontier exploration
- Scenario Modeling and Comparison: What-if network configurations
- Network Visualization: Geographic and flow visualization
Input Schema
network_optimization_request:
network_elements:
suppliers: array
facilities: array
- facility_id: string
type: string # plant, DC, hub
location: object
capacity: float
fixed_cost: float
variable_cost: float
status: string # existing, candidate
customers: array
products: array
demand_data:
customer_demand: array
seasonality: object
cost_data:
transportation_rates: array
facility_costs: object
inventory_costs: object
constraints:
service_levels: object
capacity_constraints: object
policy_constraints: array
optimization_objective: string # minimize_cost, maximize_service, balanced
scenarios: array
Output Schema
network_optimization_output:
optimal_network:
facilities:
open_facilities: array
closed_facilities: array
capacity_utilization: object
flows:
sourcing_flows: array
distribution_flows: array
inventory_positioning: object
cost_analysis:
total_cost: float
transportation_cost: float
facility_cost: float
inventory_cost: float
cost_breakdown: object
service_analysis:
service_levels_achieved: object
lead_times: object
scenario_comparison: array
- scenario_name: string
total_cost: float
service_level: float
trade_offs: array
sensitivity_analysis:
key_drivers: array
break_even_points: object
visualizations:
network_map: object
flow_diagram: object
cost_service_curve: object
implementation_roadmap: object
Usage
Greenfield Network Design
Input: Customer locations, demand, candidate sites
Process: Optimize facility locations and flows
Output: Optimal network configuration with cost analysis
Distribution Network Optimization
Input: Existing network, new demand patterns
Process: Evaluate reconfiguration options
Output: Recommended network changes with savings
Scenario Analysis
Input: Multiple demand/cost scenarios
Process: Optimize network for each scenario
Output: Robust network recommendation
Integration Points
- Optimization Solvers: AIMMS, Llamasoft, CPLEX, Gurobi
- GIS Platforms: Geographic analysis and visualization
- ERP Systems: Demand and cost data
- Tools/Libraries: AIMMS, Llamasoft, CPLEX, Gurobi, or-tools
Process Dependencies
- Supply Chain Network Design
- Supply Chain Cost-to-Serve Analysis
- Capacity Planning and Constraint Management
Best Practices
- Validate model inputs thoroughly
- Consider multiple scenarios and sensitivities
- Balance optimization with practical constraints
- Involve operations in solution validation
- Plan phased implementation approach
- Monitor actual vs. modeled performance