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For stochastic optimisation algorithms, knowing the probability distribution with which
an algorithm allocates new samples in the search space is very important, since this explains
how the algorithm really works and is a prerequisite to being able to match algorithms to
problems. This is the...
This study proposes an orthogonal momentum-type
particle swarm optimization (PSO) that finds good
solutions to global optimization problems using a delta
momentum rule to update the flying velocity of particles
and incorporating a fractional factorial...
This paper presents a macrocell placement constraint and overlap removal methodology using an improved particle swarm optimization (PSO). Several techniques have been proposed to improve PSO, such as methods to prevent the floorplan from falling into the local minimum and to...
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