Akugbe Martins Arasomwan

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This paper establishes that the basic particle swarm optimisation (BPSO) technique can perform efficiently without some (or any) of the control parameters in the particle velocity update formula and also presenting a modified BPSO (M-BPSO) that ameliorate the problem of premature convergence associated with PSO when optimising high dimensional multi-modal(More)
Inertia weight is one of the control parameters that influence the performance of Particle Swarm Optimization (PSO). Since the introduction of the inertia weight parameter into PSO technique, different inertia weight strategies have been proposed to enhance the performance of PSO in handling optimization problems. Each of these inertia weights has shown(More)
From the inception of Particle Swarm Optimization (PSO) technique, a lot of work has been done by researchers to enhance its efficiency in handling optimization problems. However, one of the general operations of the algorithm still remains - obtaining global best solution from the personal best solutions of particles in a greedy manner. This is very common(More)
This paper reports the performance of particle swarm optimization (PSO) for the assignment of blood to meet patients' blood transfusion requests for blood transfusion. While the drive for blood donation lingers, there is need for effective and efficient management of available blood in blood banking systems. Moreover, inherent danger of transfusing wrong(More)
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