Name
Abstract | ||
|---|---|---|
Self-organized Invasive Parallel Optimization (SIPO) is a new framework for solving optimization problems on parallel platforms. In contrast to existing approaches, the resources in SIPO are self-organized and represented as a unified resource to the user who specifies the optimization problem and its preferences to the system. SIPO starts working with one resource and automatically divides the optimization task stepwise into smaller tasks which are assigned to more resources. This job assignment is decided on demand by the resources. The novelty here is that there is no need to specify the number of parallel computing resources in the beginning of the optimization. This number is estimated during the optimization process by the resources. The proposed new framework of SIPO is described in this paper with respect to multi-objective optimization problems but it has a much larger scope. A comparative evaluation of using SIPO in multi-objective optimization problems shows that this adaptive approach can obtain equally good or sometimes even better solutions than other parallel and non-parallel methods which are not self-organized. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1145/1998570.1998581 | Proceedings of the 3rd workshop on Biologically inspired algorithms for distributed systems |
Keywords | DocType | Citations |
multi-objective optimization problem,parallel optimization,optimization task stepwise,self-organized invasive parallel optimization,proposed new framework,new framework,optimization problem,unified resource,parallel computing resource,parallel platform,optimization process,self organization,parallel computer | Conference | 1 |
PageRank | References | Authors |
0.36 | 14 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sanaz Mostaghim | 1 | 432 | 41.17 |
| Friederike Pfeiffer | 2 | 1 | 0.36 |
| Hartmut Schmeck | 3 | 1034 | 120.58 |