Non-Linear Multi-Objective Optimization of a Supply Chain Under Flexible Constraints

Design an AI system that optimizes the logistics network between manufacturing sites and their consumer zones while maximizing Operating Income.

PROs & benefits

Best distribute production —as much as possible— to maximize income.

Systematically and quickly find the best parameters of the supply chain, considering contradictory and constrained objectives (quantities to be produced, inventory costs, transportation costs…).

Ultimately, simplify the organization of manufacturing sites and avoid transporting unnecessary loads and traveling over long distances.

Respect ecological regulations while maintaining income level.


XTRACTIS OPTIMIZE robots explore the 27-dimension decision space of possible quantities of goods to produce and ship from 3 manufacturing sites to 3 consumer zones to best maximize Operating Income.

The Use Case tests OPTIMIZE for 4 different scenarios defined by requests on local sales objectives, local supply constraints, and ecological transport requirements. Objectives and constraints are either fuzzy (flexible) or binary (rigid).

Use Case 2023/09 (v1.8)

Powered by XTRACTIS® OPTIMIZE 13.0.46103 (2023/06)


  1. Use Case Objectives
  2. Work Hypotheses
  3. XTRACTIS Operational Research Process
  4. Discovery of the Most Optimal Solution — SCENARIO #1
  5. Discovery of the Most Optimal Solution — SCENARIO #2
  6. Discovery of the Most Optimal Solution — SCENARIO #3
  7. Discovery of the Most Optimal Solution — SCENARIO #4
  8. Appendices