Modeling Framework for Uncovering System Behaviors in Biofuels Supply Chain Network

Abstract

A full realization of alternative energy such as biofuels depends on the existence of a viable supply chain (SC) network. This work seeks to understand the dynamics of biofuels SC network by developing an approach to model the dynamics and characterize system behavior. A multi-actor approach is pursued in which the interests of three supply chain actors are represented: users, biorefineries, and farmers with a simple binary decision option: adoption or non-adoption of biofuels. The decision dynamics of these actors is modeled using a computational ecosystem construct. This SC network model is characterized by distributed control, time asynchrony, and resource contention among actors who interact in collaborative and competitive mode and who make decision based on incomplete knowledge and delayed information. A preliminary set of coupled payoff function for each actor type and each decision is developed to represent interdependencies among SC actors. It also serves as a mechanism to incorporate the effects of policy interventions and other exogenous factors. The SC network shows behavior ranging from fixed point equilibrium under no delay and perfect knowledge to periodic and chaotic oscillations. It is very sensitive to the time delay parameters that partly influence the quality of information on which actors’ decision are based. Using non-linear time series analysis, several regions of SC behavior are identified. In particular, chaotic behavior was observed. The work provides a basis for further development including identification of policies to control undesirable behaviors.