With the increasing expectation from patients and the regulations enacted by the government, exploring ways to shorten patient journey has caught increasing attention. Patient journey optimization typically involves the coordination of treatment scheduling at multiple medical units. This decentralized nature of the problem makes conventional centralized operation research methods hard to be applied and motivates the use of the multi-agent approach. In this paper, we focus on cancer patient treatment. We model patients and medical units as autonomous agents which interact locally via a bidding process and a coordination process for patient journey optimization. With reference to a dataset containing more than five thousand cancer patient journeys, the effectiveness of the proposed algorithm under different settings of implementation has been evaluated via experimental simulations.