Research On Scheduling Optimization Models And Corresponding Algorithms For Container Terminal Under Abnormal Working Conditions

The production organization optimization of container terminal has always been a research hotspot.The existing researches mainly focus on the scheduling optimization under normal working conditions.However,in practice,due to the impact of various emergencies,the container terminal often has to face abnormal working conditions,which becomes a major problem to improve the port management level.If enough attention and timely response are not given,the port operation efficiency will reduce,the operating cost will increase,and the satisfaction of the shipping company will be affected.Hence,combined with the specific characteristics of the container terminal scheduling problems,the causes of the abnormal working conditions such as the equipment failure such as crane quay,the planning of unscheduled ships and the operation resumption after the temporary shutdown of the container terminal are analyzed,and the interest conflicts between the shipping company and the port side under different abnormal working conditions are expounded.From the perspective of comprehensive consideration of the interests of all parties,the corresponding multiple objective optimization models are constructed,and the solving methods combining the characteristics of the problems are designed.And the details are as follows:(1)In order to take the interests of all parties into account,a multiple objective optimization model is established to solve the problem,and a quantitative method for the bais degree of each Pareto non-inferior solution corresponding to each optimization objective is proposed.Based on the geometric distribution features of Pareto front,the effective information hidden in Pareto front is mined,and some new concepts such as average variability,sensitivity ratio,dimensionless sensitivity ratio,bais degree,unbalance degree are established.Finally,the quantification of the bais degree of each Pareto non-inferior solution corresponding to each optimization objective is realized,and the solution with the minimal unbalance degree corresponding to each optimization objective is found,which can provide necessary quantitative decision basis for decision makers.(2)For the abnormal working conditions caused by equipment failure,a multiple objective optimization model is established to minimize the deviation of departure time,the terminal operation cost and the deviation degree from the original operation plan.In order to improve the performance of the algorithm,the crossover operation and mutation operation of the algorithm are improved on the basis of NSGA-II algorithm.The incomplete two points crossover operation and incomplete single point mutation operation are adopted,and the neighborhood search rule of crane quay sharing is considered.The Pareto non-inferior solution set satisfying the constraints is calculated.In order to find a scheduling scheme that takes the minimal deviation of departure time,the minimal terminal operating cost and the minimal deviation degree of operation plan into account,the proposed method in this paper to quantify the bias degree of each Pareto non-inferior solution corresponding to each objective is used,and the scheme with the minimal unbalance degree corresponding to each objective is obtained.(3)For the abnormal working conditions of unscheduled ships arriving at the port,a biobjective optimization model is established aiming at the maximal customer satisfaction of the shipping company and the minimal extra operating cost of the terminal.And the Pareto non-inferior solution set is calculated by improving the initial point selection rule of the plant growth simulation algorithm,replacing the fixed step with the mixed step search,and adding the hierarchical non-dominated sorting.In order to find a scheduling scheme that takes both the maximal customer satisfaction of the shipping company and the minimal extra operating cost into account,the proposed method in this paper to quantify the bias degree of each Pareto non-inferior solution corresponding to each objective is used,and the scheme with the minimal unbalance degree corresponding to the two objectives is obtained.(4)For the abnormal working conditions of operation resumption after the temporary shutdown of the container terminal,a biobjective optimization model is established to minimize the ship waiting time and the extra operation cost of the port.On the basis of particle swarm optimization algorithm,the coding and decoding of the algorithm are designed.According to the characteristics of the problem,the process of particle updating and inertia weight changing of the original algorithm is improved,and the neighborhood search rules based on the strategy of increasing or decreasing the number of equipped crane quays and reducing the deviation from the optimal berth position are added.The Pareto non-inferior solution set satisfying the constraints is calculated.In order to find a scheduling scheme which can satisfy the minimal waiting time and the minimal additional operation cost of the port side,the proposed method in this paper to quantify the bias degree of each Pareto non-inferior solution corresponding to each objective is used,and the scheme with the minimal unbalance degree corresponding to the two objectives is obtained.In this paper,the theory and methods of multiple objective optimization problem are applied to practice,which not only helps solve the schelduing optimization problems of considering both interests of the ship company and the port side,but also enriches the decision-making method of multiple objective optimization problems.The research in this paper can provide effective optimization methods and solving approaches for the formulation and adjustment of scheduling schemes,and has important application value for improving the management level of port enterprises.