

![0_image_0.png](0_image_0.png) 

K = 2 and q = 2 is 21.**3. Thus, the neutral degree is high on the Olympus**
and this should be exploited to design metaheuristics fitting the problem.

## 5.2.2 Fitness Distance Correlation

FDC has been calculated on a sample of 4000 randomly chosen solutions belonging to the Olympus. Results are summarized in table 7. The first six lines of this table reports the FDC where distance is calculated from one particular solution in the blok′**. The line before last reports FDC where distance**
is computed from the nearest optimum for each individual belonging to the sample. The last line is the FDC, relative to euclidean distance, to the centroid C
′
. Two samples of solutions were generated: Osample**, where solutions are**
randomly chosen in the Olympus and Csample**, where each bit of a solution**
has probability to be '1' according to the centroid distribution.

With the sample based on the Olympus, the FDC is lower, meaning that improvement is easier for the blok′**than for the overall landscape (see section 4.2)**
except for Coe1. FDC with GLK′, ABK′**, nearest, or** C
′
**is over the threshold**
−0.**15. For Csample, all the FDC values are lower than on Osample. Also,**
except for Coe1
′
, the FDC is over the limit −0.**15. This correlation shows that**
fitness gives useful information to reach the local optima. Moreover, as the FDC from the centroid is high (see also figure 15), fitness leads to the centroid C
′
**. We can conclude that on the Olympus, fitness is a reliable guide to drive**
searcher toward the blok′**and its centroid.**