An improved niche genetic algorithm based on simulated annealing: SANGA
Huanyang Zheng · 2011 International Conference on Computational Problem-Solving (ICCP) · 2011
A simulated annealing based niche genetic algorithm (SANGA) has been presented to strength the optimization ability of niche genetic algorithm (NGA). The improved idea is to define niche formation using probability condition rather than simply distance condition. Individuals who only have close neighbors are inclined to build up niche; individuals who only have far neighbors are likely to depart from niche. The feasibility and validity of the proposed method is proved by the contrast between current NGA based on penalty, NGA based on fitness sharing, NGA based on deterministic crowding and SANGA in some simulation experiments and applications of 0-1 knapsack problem.