Implementation of golden section search algorithm on artificial bee colony variants

Nature-inspired computing (NIC) is the collection of computing method inspired from nature or inspired by the progressions that happens in nature. Swarm Algorithms are based on schemes which make use of features of collective cleverness. The investigation of computational frameworks persuaded by the ‘collective intelligence’ is termed as Swarm intelligence. Artificial Bee Colony Algorithm (ABC) is the latest development system to take care of numerous numerical issues and engineering issues. The inspiration behind this can be Nature, wherever issues area unit solved on the premise of nature of swarm such as ants, bees etc. The hunting behavior of bees plays a crucial role whereas approaching ABCs algorithms. Here a new approach is purposed where features of artificial bee colony are improved with the help of modification in existing algorithms and then this modified algorithm is hybrid with Golden Section search algorithms. This calculative methodology is tried over some benchmark capacities and some understood designing issues. On the premise of highlight like achievement rate, mean capacity assessment, satisfactory lapse and so forth a correlation graph is made which demonstrate the execution assessment of these calculations.