Pengukuran Kinerja Partially Mapped Crossover dan Cycle Crossover pada Genetic Algorithm

Abstract

Traveling Salesman Problem (TSP) is a classical combinatorial optimization problem which is becoming a standard for testing computational algorithm. Many methods can be used to solve the TSP, one of which is a Genetic Algorithm. Genetic Algorithm generates a population of candicate solutions comeptition (route) and then cause them to evolve through a process of natural selection. Bad solutions tend to die, while better solutions survive and reproduce. By repeating this process over and over again Genetic Algorithm spawned an optimal solution (the shortest route) on the TSP Problem. However, the performance of Genetic Algorithm is heavily influenced by its Operator and parameters. One of the Genetic Algorithm’s operator is crossover operators. Partially Mapped crossover (PMX) and cycle Crossover (CX) is a commonly used method of crossover for TSP problems