Solving Multidimensional Knapsack Problem with Bayesian Multiploid Genetic Algorithm

Authors : Emrullah GAZİOĞLU

Pages : 58-64

Doi:10.55195/jscai.1216193

View : 11 | Download : 10

Publication Date : 2022-12-28

Article Type : Research Paper

Abstract :Solving optimization problems is still a big challenge in the area of optimization algorithms. Many proposed algorithms in the literature don’t consider the relations between the variables of the nature of the problem. However, a recently published algorithm, called “Bayesian Multiploid Genetic Algorithm” exploits the relations between the variables and then solves the given problem. It also uses more than one genotype unlike the simple Genetic Algorithm insert ignore into journalissuearticles values(GA); and it acts like an implicit memory in order to remember the old but good solutions. In this work, the well-known Multidimensional Knapsack Problem insert ignore into journalissuearticles values(MKP); is solved by the Bayesian Multiploid Genetic Algorithm. And the results show that exploiting relations between the variables gets a huge advantage in solving the given problem.
Keywords : genetic algorithm, evolutionary computing, multidimensional knapsack problem