Abstract
The problem we aim to solve in this study is the distributed resource allocation problem (DRAP) over unbalanced directed networks, in which the local inequality constraint and global equality constraint are considered. On the basis of the fixed-time projection method, a distributed gradient algorithm is developed. The corresponding eigenvalue is obtained within fixed-time by tapping the row-stochastic or column-stochastic Laplacian matrix to overcome the unbalance of directed weights. Therefore, the optimal solution can be obtained asymptotically. Moreover, the proposed algorithm is initialization-free and its control parameters are constant. Finally, the effectiveness is illustrated by several case studies.
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