OG (objective guide) means that the I&D components are solely guided by the objective function, NOG (non-objective guide) means the I&D components are solely guided by one or more functions other than the objective function, and R (randomness) means the I&D components are solely guided by randomness. For example, the selective strategy, i.e. roulette wheel selection, exemplifies the effect of OG in terms of the fitness value of the solutions. The corner OG corresponds to I&D components with a maximum intensification effect and a minimum diversification effect. On the other hand, corners NOG, R and the segment between the two corners correspond to I&D components with a maximum diversification effect and a minimum intensification effect. All I&D components can be located somewhere on or in between the three corners. In step with the OG gradient, the less an I&D component uses the objective function, the further away from corner OG it has to be located. The same explanation applies to the gradient of NOG and R.
As explained in the above sections, we attempt to summarize the basic I&D components that are inherent to the above SI algorithms. For example, the pheromone update component in ACO has the effect of changing the probability distribution that is used to sample the search space. It is guided by the objective function (solution components found in better solutions than others are updated with a higher amount of pheromone) and it is also influenced by a function applying pheromone evaporation. From this perspective, this component is located on the line between corners OG and NOG. Provided that the evaporation function is relatively fixed, this component should be closer to the corner OG. In other words, the effect of this mechanism is basically the intensification of the search, but there is also a diversifying component that depends on the greediness of the pheromone update (the less greedy or deterministic, the higher is the diversifying effect). In some ACO variants, the evaporation function may even be dynamic, which leads to the dynamic trade-off between the effect of intensification and diversification. Referring to the Section 4, the I&D components and their intrinsic force are summarized in the Table 5.