Optimization of Cargo Handling Machinery Allocation and Ship Traffic Organization for Bulk Cargo Ports

A model for bulk cargo ports to optimize cargo handling machinery allocation and ship traffic organization is introduced. A multi-objective genetic algorithm based on heuristic screen rules (MOGA-HSR) is designed. The algorithm integrates the traffic organization rules for one-way waterway and the cargo-ship matching rules. The self-adaptive crossover and mutation probability function is introduced to accelerate the convergence process. Simulations of Huanghua Coal Port are performed with MOGA-HSR and genetic algorithm for non-dominated sorting with elitist strategy (NSGA-Ⅱ), respectively. The simulation results show that the overall entering-leaving time and ship waiting time for the former are 2.7 % and 2.5 % shorter compared to those for the latter.And compared to the principle of first come first served (FCFS), they are shortened by 38 % and 30.8 % respectively, which demonstrated the effectiveness of the new method.