| The operation process of an automated container terminal requires a variety of complex equipment to work together,which requires the manager to make a reasonable scheduling plan to avoid possible equipment conflicts and delivery delays,and to improve operational efficiency.Among the subsystems of an automated terminal,the handling system and the transportation system need to operate containers frequently,which has the greatest impact on the operation of the terminal.In this paper,the "double cycle" mode of quay crane are adopted,and the AGV is taken as the scheduling optimization object of terminal to coordinate the operation of quay crane,yard crane and other resources,so as to provide a reasonable solution for the integrated operation of the automated terminal.In view of the practical problems such as multi-resource scheduling conflicts and AGV charging affecting system efficiency in automated container terminals,this paper takes into account the impact of AGV charging in the actual operation of terminals,studies the multi-resource collaborative scheduling in automated terminals under the "double cycle" mode,and aims at balancing time efficiency and energy saving to improve the multi-resource collaborative scheduling ability.It is of great practical significance to promote the intelligent and low-carbon development of automated terminal.Based on similar research and analysis at home and abroad,this paper takes the traditional blocking hybrid flow shop scheduling theory and its corresponding modeling and solving methods as the research basis,and takes minimizing the makespan and comprehensive transportation energy consumption of quay crane as the scheduling optimization objectives.A mixed integer nonlinear model for collaborative scheduling optimization of automated terminals is established considering various constraints such as charging,continuity between import and export tasks,equipment resources,and working time of tasks in the actual operation of AGV.A simple and reasonable initial solution is designed based on the characteristics of the problems in this paper.An improved genetic algorithm(SA-GA)with simulated annealing mechanism was designed and used to solve the problem.SA-GA not only uses the advantage of simulated annealing algorithm to avoid the shortage of genetic algorithm to converge in advance and fall into the local optimal solution,but also retains the high efficiency of genetic algorithm.Example analysis shows that the effectiveness of SA-GA is verified by comparing with the exact solution of commercial solver Gurobi in small-scale examples.In the case of large-scale calculation,combining the performance evaluation indexes of Num,ER and C algorithms,and comparing with multi-objective simulated annealing(MOSA)and multi-objective genetic algorithm(NSGA-Ⅱ),SA-GA can obtain better distributive and convergent Pareto solution sets,and provide a more reasonable AGV scheduling scheme.The multi-resource cooperative scheduling optimization model and algorithm proposed in this paper realize the overall optimization of the operating system of the automated terminal under the "double cycle" mode,and can provide model and algorithm reference for improving utilization of resources of the automated terminal,reducing energy saving and emission reduction. |
