Abstract
This article addresses the optimization problem with its global objective function being composed of multiple convex functions under multiple nonidentical local constraints. The specific purpose is to resolve the studied optimization problem in a distributed manner in the presence of the time-varying unbalanced graph sequence. For this purpose, an efficient distributed discrete-time algorithm is developed over the time-varying unbalanced graph sequence by improving the classical push-pull algorithms. Moreover, for the developed distributed discrete-time algorithm, a rigorous analysis is made of its convergence property to the optimal solution as well as its convergence rate under some standard assumptions. Finally, numerical simulations are carried out to demonstrate the good performance of the designed algorithm.
| Original language | English |
|---|---|
| Pages (from-to) | 387-402 |
| Number of pages | 16 |
| Journal | IEEE Transactions on Control of Network Systems |
| Volume | 12 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 2025 |
Bibliographical note
Publisher Copyright:© 2014 IEEE.
Keywords
- Distributed optimization algorithm
- improved push-pull framework
- multiple local constraints
- time-varying unbalanced graphs
- Consensus algorithm
- Graph algorithms
- Distributed optimization
- Graph sequences
- Improved push-pull framework
- Local constraints
- Multiple local constraint
- Optimization algorithms
- Optimization problems
- Push pull
- Time varying
- Time-varying unbalanced graph
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