Abstract
In this paper, we consider a multi-machine multi-period resource allocation problem among multiple agents, each of which is responsible to solve a flowshop scheduling problem. We present an iterated combinatorial auction approach in which bid generation is performed within each agent, and the concept of utility pricing is then applied in the process of price adjustment. We compare with the conventional price adjustment scheme proposed in Fisher (1985), and show better convergence properties. Experimentally, we compare our approach against an integer programming model as well as conventional price adjustment schemes, and achieve drastic run time improvement.
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