Optimizing Cargo Ship Operational Costs: A Comprehensive Algorithmic Approach

Cargo ships are essential in global trade, and their operational expenses strongly influence the economic sustainability of shipping companies. The objective is to minimize the total cost function, expressed as 0.2(x2) + (450/x),, where ‘x’ represents the ship speed. The study explores the optimal ship speed within the specified constraints of 0.5 m/s to 25.5 m/s using algorithms such as Particle Swarm Optimization (PSO), Simulated Annealing, Stochastic Gradient Descent, and Newton’s Method. Performance metrics, including Mean Squared Error (MSE), R-squared, and convergence plots, are employed to assess the efficiency of these optimization strategies. The research depicts that Newton’s Method outperforms others based on comprehensive metric analysis. The findings contribute valuable insights to streamline cargo ship fleet management, offering practical solutions for improving economic sustainability in the maritime industry.