by saifulazimi | Jul 21, 2020 | Single & Multi-Objective Algorithms
Non-dominated Sorting Genetic Algorithm using Reference Point Based (NSGA-III) was designed by Deb in 2014 to solve the crowding distance issue in NSGA-II. The designed NSGA-III has a similar framework as the NSGA-II. In designing the NSGA-III, significant changes in...
by saifulazimi | Jul 21, 2020 | Single & Multi-Objective Algorithms
Non-dominated Sorting Genetic Algorithm II (NSGA-II) is a variant of MOGA that are designed to improve its previous version called Non-dominated Sorting Genetic Algorithm I (NSGA-I). NSGA-II was proposed by Deb to improve the efficiency of individual classification in...
by saifulazimi | Jul 21, 2020 | Research, Single & Multi-Objective Algorithms
Multi-objective Genetic Algorithm (MOGA) was proposed by Carlos and Peter which was inspired by the population genetics and the evolution of genes at the population level. In MOGA, the rank of an individual is relating to the number of chromosomes in the current...
by saifulazimi | Jul 21, 2020 | Single & Multi-Objective Algorithms
Particle Swarm Optimization (PSO) is one of the Evolutionary Algorithm (EA) that was develop and proposed by Kennedy and Eberhart based on the inspiration from flock of birds which the main aim is to find food. This algorithm implementation has solved a wide variety...
by saifulazimi | Jul 21, 2020 | Single & Multi-Objective Algorithms
Ant Colony Optimization (ACO) algorithm is one of the optimization algorithms that is inspired by the foraging behaviour of real ant colonies. When the ants searching the food, they initially explore the area randomly. Then, a chemical pheromone trail will be left on...
by saifulazimi | Jul 21, 2020 | Single & Multi-Objective Algorithms
Simulated Annealing (SA) algorithm was originally inspired from the metal work annealing process. This algorithm was designed to be implemented in the combinatorial optimization problems and it has been adapted to be implemented for continuous optimization problems....
