Why is there no role for relaxation bounding here

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Particle swarm optimization can be applied to global optimization, as follows.

The goal is to search a space of many dimensions for the best solution. A swarm of particles are initially distributed randomly through the space.

Certain particles have two-way communication with certain others.

In each iteration, each particle moves randomly to another position, but with higher probability of moving closer to a communicating particle that occupies a good solution.

After many iterations, the best solution found is selected.

How can this process be viewed as enumerating a sequence of problem restrictions? Why is there no role for relaxation bounding here?

Reference no: EM131168680

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