A NEW GENETIC ALGORITHM TO SOLVE KNAPSACK PROBLEMS

Knapsack problem is a well-known class of optimization problems, which seeks to maximize the benefit of objects in a knapsack without exceeding its capacity. Various knapsack problems have been tried to be solved by decision makers a wide range of fields, the most important one of these is portfolio optimization. In recent few decades, heuristic methods have been widely used to solve hard optimization problems since they have proved their success in many real life applications. Genetic algorithm is one of these heuristic algorithms which have been successfully employed in a variety of continuous, discrete and combinatorial optimization problems. In this study, a new genetic algorithm is improved to solve a portfolio optimization problem efficiently.