This paper presents a novel nature-inspired multi-objectiveoptimization algorithm. The method extends the glowworm swarm particlesoptimization algorithm with algorithmical enhancements which allowto identify optimal pareto front in the objectives space. In addition,the system allows to specify constraining functions which are needed inpractical applications. The framework has been applied to the powerdispatch problem of distribution systems including Distributed EnergyResources (DER). Results for the test cases are reported and discussedelucidating both numerical and complexity analysis.
|Title of host publication||Applications of Evolutionary Computation|
|Number of pages||10|
|Publication status||Published - 2013|
|Name||LECTURE NOTES IN COMPUTER SCIENCE|
- Theoretical Computer Science
- General Computer Science