Abstract
Gauss-Seidel type relaxation techniques are applied in the context of strictly convex network optimization problems. The algorithm lends itself for processing in a massively distributed environment. A synchronous relaxation method (SRM) is proposed, based on the k-coloring properties of the network graph. The method is tested in a simulated distributed environment on a sequential machine. Lower bounds for the expected efficiency of SRM are developed and compared with its performance as obtained through computional experiments.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 45-56 |
| Number of pages | 12 |
| Journal | Parallel Computing |
| Volume | 6 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jan 1988 |
All Science Journal Classification (ASJC) codes
- Software
- Theoretical Computer Science
- Hardware and Architecture
- Computer Networks and Communications
- Computer Graphics and Computer-Aided Design
- Artificial Intelligence
Keywords
- Networks
- distributed systems
- nonlinear programming
- optimization
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