Modeling Adaptive Market Mechanisms for Industrial Symbiosis
le 28 octobre 2025
12h45
Manufacture des Tabacs Salle MH003
Matthieu Mastio - post-doctorant SMAC team, IRIT
Abstract: Industrial Symbiosis transforms one company’s waste into another’s resource, promoting circular economy goals through local byproduct exchanges. Yet, such collaborations rarely emerge spontaneously due to coordination, economic, and spatial constraints. This work introduces a spatially explicit multi-agent model simulating decentralized byproduct markets, where firms autonomously negotiate prices and quantities through multilateral auctions. Sellers adapt their pricing strategies via reinforcement learning, while buyers select offers that maximize utility under transport and cost limitations. The model endogenously generates transaction prices and traded quantities, allowing the study of emergent circularity patterns. Simulation results show that adaptive learning enables firms to reach near-equilibrium outcomes and improve local symbiosis efficiency. Policy-oriented analyses reveal how transport costs, landfill penalties, and firm density shape circular performance. Overall, this work offers both a methodological advance in decentralized spacial market modeling and practical insights to support policy design for circular economies.
En appuyant sur le bouton "j'accepte" vous nous autorisez à déposer des cookies afin de mesurer l'audience de notre site. Ces données sont à notre seul usage et ne sont pas communiquées. Consultez notre politique relative aux cookies
