The surge in electronic procurement is fostering the proliferation of electronic marketplaces and advanced auctions as primary coordination mechanisms. Among these, combinatorial and double auctions are gaining traction in the procurement sector. However, prevalent implementations often assume participants to be perfectly rational, adhering to predefined behaviors within the auction model. These centralized models, while prevalent, fail to capture the intricate dynamics of real auction environments adequately. Consequently, there is a growing recognition of the necessity for decentralized models within an agentbased framework to simulate such auctions authentically. The contribution of this work is the application of the DEVS formalism to develop a decentralized model for a combinatorial iterative double auction to address the limitations of centralized implementations. The model is formally defined, and a case study is presented to verify it against its centralized version. This is the first step toward accommodating agents with varied behavioral patterns within auction simulations.
