Moth Swarm Algorithm (MSA)

MSA is a new metaheuristic algorithm for solving single-objective problems

Moth Swarm Algorithm (MSA): A new high-level algorithm, inspired by the orientation of moths towards moonlight.
Two novel optimization operators have been proposed:
(1) Dynamic selection strategy of crossover points based on population diversity to handle the difference vectors Lévy-mutation to improve exploration ability in the reconnaissance phase.
(2) Associative learning mechanism with immediate memory. Simulate short-term memory of moth, reduces the required memory and overcomes the initial velocity problem of classical-PSO. This mechanism is used for narrow scope exploitation in the celestial navigation phase.
This code demonstrates how MSA works for twenty-three commonly used benchmarks.
For more info please refer to:
Mohamed, A. A. A., El-Gaafary, A. A., Mohamed, Y. S., & Hemeida, A. M. (2017). Optimal power flow using moth swarm algorithm. Electric Power Systems Research, 142, 190–206. DOI: http://dx.doi.org/10.1016/j.epsr.2016.09.025
(http://www.sciencedirect.com/science/article/pii/S0378779616303765)