在船舶大型化的发展以及港口资源日益紧张的趋势下,拖轮调度作为减少港口拥堵与节约港口资源的重要手段,成为当前亟待解决的问题.通过以拖轮空驶燃油成本与拖轮助航燃油成本为目标函数,构建多停泊基地条件下的多目标拖轮调度模型,提出一种混合小生境灰狼算法(Hybrid Niche Grey Wolf Optimiza-tion,HNGWO)进行求解,针对拖轮调度问题的整数规划特点引入交叉修正更新策略,以加强算法的收敛性能,最后分别采用CPLEX、GA、PSO、GWO、HNGWO对多规模算例的求解结果进行对比分析.结果表明,HNGWO相比于GA、PSO的最优值平均优化比例可达 5.07％,相比于 GWO 的收敛速度平均优化比例为13.23％,并输出中等规模下的收敛曲线与最优调度方案甘特图,直观展示了改进算法的求解效果与收敛速度,为提高港口通行效率与经济效益提供了参考方案.
Research on Port Tug Scheduling Based on Improved Grey Wolf Algorithm
With the development of larger ships and the trend of increasingly tight port resources,tugboat scheduling,as an important means to reduce port congestion and save port resources,has become an urgent problem to be solved.By constructing a multi-objective tug scheduling model under the condition of multiple berthing bases with tug idling fuel cost and tug navigational aid fuel cost as the objective functions,a hybrid niche gray wolf algorithm is proposed for solving the problem,and a cross-correction update strategy is introduced for the integer programming characteristics of the tug scheduling problem to enhance the convergence performance of the algorithm,and finally,HNGWO,GWO,GA,and CPLEX are used to analyze the results of multi-scale calcula-tion.The results show that HNGWO can optimize 5.07％of the average optimization ratio of optimal value,compared with GA and PSO,and 13.23％of the convergence speed,compared with GWO,and output the convergence curve and Gantt chart of the opti-mal scheduling scheme at medium scale,which visually demonstrates the solution effect and convergence speed of the improved algo-rithm,and provides a reference scheme for improving the port traffic efficiency and economic benefit.
tugboat schedulingone-way channelmultiple berthing basesMulti-objective optimizationgray wolf optimiza-tion algorithm
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维普
