Global optimisation using Pareto cuckoo search algorithm
Mahlaku Mareli, Bhekisipho Twala · International Journal of Advanced Computer Research · 2017
It is important to reach an optimal way of doing things in the real world because resources are normally limited.Optimisation is about reaching better results using resources available.Some examples of optimisation include, but not limited to electricity network operation, electricity generation, wireless communications routing and minimization of energy losses during electricity transmission.Proper validations of optimisation algorithms require assessment of computational time and convergence rate in addition to the accuracy to determine the minimum or maximum values [1][2][3][4][5][6][7].Cuckoo search (CS) algorithms have proved to be more effective than other nature-inspired algorithms in solving complex problems [8,9].The original CS algorithm step sizes are derived from the Levy probability distribution function.However, some researchers have managed to improve the performance of CS by using different probability distributions to determine step sizes.