In this paper, assuming that disruptions in a supply chain result from uncertain demands, we formulate a profit maximization problem of the supply chain as a two-stage model with the decisions on facility opening at the first stage and the decisions on material flows at the second stage after realization of the demands. For such the decision problem in the supply chain, we present a formulation based on the fractile model taking into account the risk attitude of a supply chain manager. We verify the effectiveness of the proposed model by solving problems with different volatilities on the demand data.
The distributed cooperative full-state observer estimates the state of a system based on local estimations via local sensors and information exchange among local estimators. An asynchronously distributed cooperative full-state observer is proposed based on a broadcast gossip algorithm, which randomly selects communication time and communication nodes. Convergence on the first and second moments of estimation error is analyzed, and it is shown that there always exists an appropriate communication setting for convergence.