Improving Performance Genetic Algorithm on Knapsack Problem by Setting Parameter

Abstract

This paper presents a solution for the knapsack problem which uses a genetic algorithm. Knapsack is combinatorial which is to find a good solution with constraint. In reality, this problem often happens. Unfortunately, making a good solution for this issue is not as easy as it is. In this research, it applied the genetic algorithm to find a good solution for that. The process is that a set of items with weight and value, then the selection of the items to be inserted into the backpack (knapsack) with limited capacity. So the items weighing should be smaller or equal to the capacity of the backpack, but the total value is as large as possible. A genetic algorithm is a heuristic searching algorithm based on natural selection of mechanism and nature genetics. The result suggests that the genetic algorithm can do a better performance than other comparable models by setting GA parameter.