Advances, Systems and Applications
Table 2 The specific algorithm parameters
From: Cost-based hierarchy genetic algorithm for service scheduling in robot cloud platform
Parameter | Value |
|---|---|
Number of particles (DNPSO) | 25 |
Min position(DNPSO) | 0 |
c1(DNPSO) | 2 |
c2 (DNPSO) | 2 |
Population size(GATS) | 25 |
Mutation rate(GATS,RHGA) | 0.01 |
Crossover rate(GATS,RHGA) | 0.8 |
Number of generations(DNPSO,GATS,RHGA) | 1000 |
the threshold of the population evolutionary factor(RHGA) | 0.3 |
selective probability(RHGA) | 0.5 |
the hunting factor of high level(RHGA) | 0.1 |
the hunting factor of middle level(RHGA) | 0.3 |
the hunting factor of low level(RHGA) | 0.6 |
the odds of crossover selection(RHGA) | 0.7 |
the similarity of parents(RHGA) | 0.6 |
Running times(Common Parameters) | 30 |
Number of services(Common Parameters) | 100-10000 |
Number of data centers(Common Parameters) | 10,30,50 |