Ship Berth Scheduling Optimization through Evolutionary Computation

The optimization of ship berth scheduling is pivots for enhancing efficiency in maritime port operations, particularl under the increasing pressures of global trade and the consequer rise in maritime traffic. This paper addresses the comple combinatorial optimization challenge of berth scheduling, whic entails assigning ships to available berths to minimize total servic time while maximizing berth and equipment utilization. We introduce an innovative Evolutionary Algorithm (EA) approach which leverages the principles of natural selection to manag multiple, conflicting objectives effectively amidst stochastic open- ational variables. In addition, a Linear Population Size Reductio (LPSR) strategy is introduced to enhance the performance. Th proposed method is validated through extensive computational experiments, demonstrating superior performance in operational efficiency and scalability compared to existing methods.