Selection Of The Best Ship Route For Container Shipping Optimization Models Using Heuristic Algorithms

Abstract

The role of ships is very important for the world economy as a means of transporting goods both between countries and between islands. The selection of ship routes is very crucial in efforts to optimize fuel costs. Application of optimization, Genetic Algorithm and Ant Colony to solve the Asymetric Traveling Salesman Problem (ATSP) model with the minimum fuel cost objective function. This study aims to determine shipping routes for initial/final destinations with lower fuel costs. The results of research on the best route for container ships develop a Traveling Salesman Problem model for decision making for the design of maritime logistics networks with optimum operational costs. The Ant Colony algorithm provides 8 routes with lower fuel costs than the genetic algorithm and the genetic algorithm provides 2 routes with lower costs than the Ant Colony algorithm. This proves that the Ant Colony algorithm is more effective in determining ship routes with the lowest fuel costs.