Agent-Based Simulation of Integrated Process and Energy Supply Chains: A Case Study on Biofuel Production

Despite the potential benefits of decision-level integration for process and energy supply chains (SCs), these systems are traditionally assessed and optimised by incorporating simplified unit operation models within a spatially distributed network. The desired organisational-level integration cannot be achieved without leveraging complex computational tools and concepts. This work proposes a multi-scale agent-based model to facilitate the transition from traditional practices to coordinated SCs. The proposed multi-agent system framework incorporates different enterprise dimensions of the process and energy SCs, including raw material suppliers, rigorous processing plants, and consumers. The behaviour of each agent type and its interactions are implemented, and their impact on the overall system is investigated. This approach allows for the simultaneous assessment and optimisation of process and SC decisions. By integrating each decision level into the operation, the devised framework goes beyond existing studies in which the impacts of lower decision levels are neglected. A biofuel SC example comprising farmers, biorefineries, and end-users is presented to demonstrate the application of the proposed multi-agent system. The involved actors seek to increase their payoffs given their interdependencies, intra-organisational variables, and the underlying dynamics of the network. The aggregated payoff of the supply network is optimised under different scenarios, and fractions of capacity allocated to biofuel production and consumption are obtained. The results indicate that integrated decision-making significantly influences SC performance. The proposed research expounds a more realistic view of multi-scale coordination schemes in process and energy SCs.