  In this paper, the authors propose to increase the efficiency of blockchain
mining by using a population-based approach. Blockchain relies on solving
difficult mathematical problems as proof-of-work within a network before blocks
are added to the chain. Brute force approach, advocated by some as the fastest
algorithm for solving partial hash collisions and implemented in Bitcoin
blockchain, implies exhaustive, sequential search. It involves incrementing the
nonce (number) of the header by one, then taking a double SHA-256 hash at each
instance and comparing it with a target value to ascertain if lower than that
target. It excessively consumes both time and power. In this paper, the
authors, therefore, suggest using an inner for-loop for the population-based
approach. Comparison shows that it's a slightly faster approach than brute
force, with an average speed advantage of about 1.67% or 3,420 iterations per
second and 73% of the time performing better. Also, we observed that the more
the total particles deployed, the better the performance until a pivotal point.
Furthermore, a recommendation on taming the excessive use of power by networks,
like Bitcoin's, by using penalty by consensus is suggested.
