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 Krill Herd Optimization Algorithm Numerical Example What is Krill Herd Optimization Algorithm?  Krill herd optimization algorithm is introduced in 2012 to solve the Global Optimization Function. This is a population-based Swarm Intelligence Search Algorithm based on the Herding behavior of krill.   In the Krill herd optimization algorithm, we have a  Group of Krill individuals and they are  Searching for Food.  Krill Herd Optimization Algorithm Working. In real life, Krill move through Multidimensional Space to search for Food and High-Density herd. Three main Calculations to update Krill's Position.  Movement Induced by the position of other Krill’s. Foraging Activity: Krill’s Searching for Food. Random Diffusion: Net movement of each Krill based on Density. KRILL MOTION CALCULATION The movement led by Other Krill Foraging Activity/Motion Random Physical Diffusion FOR KRILL Individual Movement is Calculated as: 𝑁_𝑖^𝑁𝑒𝑤=𝑁^𝑀𝑎𝑥 𝛼_𝑖+𝜔_𝑛 𝑁_𝑖^𝑜𝑙𝑑 Where, 𝑁^𝑀𝑎𝑥 = Ma

Harris Hawks Optimization Algorithm Harris Hawks Optimization Algorithm Introduction Harris hawks optimizer (HHO) is a nature-inspired population-based optimization algorithm. Harris Hawks Optimization algorithm is a Population-based algorithm. This algorithm mimics the Exploring, Exploiting, and Attacking strategies of Harris Hawks. Harris Hawks Optimization algorithm can be used to solve different engineering problems. About Harris Hawk Harris Hawk is a large medium bird and also known as Dusky Hawk. Harris Hawk hunt in cooperative groups and group size is 2 to 7 birds. Hawks Diet: Large insects, Birds, Lizards, and Mammals. Harris Hawks Optimization Algorithm Steps-by-Step. INPUT: Population Size (N), and a maximum number of iterations (MaxT). OUTPUT: Target Location and its Fitness Values. Step 01: Initialize the population randomly 𝑋_𝑖 ( 𝑖=1,2,3,4,…𝑁 ). Step 02: Check While ( (t ≥ max )Stopping Criteria is Matched or Not ) Step 03: Calculate fitness value for each ha