Analysis of the Combination of Genetic Algorithm and Fuzzy Logic in Optimizing Ship Service Scheduling at Belawan Port

Vessel service scheduling is one of the key challenges in efficient port logistics management, which requires careful handling of variables such as capacity, time, and priority. In an effort to optimize this process, this research proposes an innovative approach that combines Genetic Algorithm (AG) and Fuzzy Logic to reduce waiting time for ship services in ports, specifically in Belawan Port, Indonesia, where this research is conducted. In this research, Genetic Algorithm, as a population-based optimization method, is used to find the optimal solution by utilizing selection, crossover, and mutation mechanisms. Meanwhile, Fuzzy Logic is applied to handle uncertainty and variability in scheduling caused by factors such as the location of the ship, the length of the ship service process, and will affect the waiting time of the ship to be served. In this research, the parent selection process in Genetic Algorithm uses tournament selection method and Fuzzy Logic with Tsukamoto method. By utilizing the power of these two algorithms, the proposed system is expected to reduce the waiting time for ships to be served. The results of this research trial show that this combined approach is able to show optimization of ship services marked by a decrease in the average waiting time for ships to be served when compared to traditional scheduling methods with a decrease in the average waiting time of 38.50475%.