Title :
Optimisation techniques for electrical power systems. II. Heuristic optimisation methods
Author :
Song, Yong-hua ; Irving, Malcolm R.
Author_Institution :
Dept. of Electron. & Comput. Eng., Brunel Univ., Uxbridge, UK
fDate :
6/1/2001 12:00:00 AM
Abstract :
For pt. I see ibid., vol.14, no.5, p.245-54 (2000). An introduction to mathematical programming based methods was given in the first tutorial of this three-part series. This second part covers major modern heuristic optimisation techniques and their integration and comparison with other methods. This paper discusses evolutionary algorithms; simulated annealing; tabu search; ant colony search; neural networks; and fuzzy programming.
Keywords :
fuzzy set theory; genetic algorithms; mathematical programming; neural nets; power system analysis computing; power systems; search problems; simulated annealing; ant colony search; electrical power systems; evolutionary algorithms; fuzzy programming; heuristic optimisation methods; mathematical programming; neural networks; simulated annealing; tabu search;
Journal_Title :
Power Engineering Journal
DOI :
10.1049/pe:20010307
