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In the original PSO, a particle’s information on its neighbourhood’s best found solution is updated after the performance of the whole swarm is evaluated.

This version of PSO algorithm is known as synchronous PSO (S-PSO).

Exploration and exploitation play important roles in determining the quality of a solution.

Exploration in asynchronous update ensures that the search space is thoroughly searched so that the area containing the best solution is discovered.

The results are statistically analysed and show that the proposed SA-PSO has performed consistently well.

Particle swarm optimisation (PSO) was introduced by Kennedy and Eberhart in 1995 [1].

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The particles move within the search area to find the optimal solution by updating their velocity and position.The proposed algorithm, which is named as the synchronous-asynchronous PSO (SA-PSO), divides the particles into smaller groups.These groups are updated asynchronously, while members within the same group are updated synchronously.Asynchronous update PSO (A-PSO) has been proposed as an alternative to S-PSO.A particle in A-PSO updates its velocity and position as soon as its own performance has been evaluated.

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