Considering the interaction between the berth and the yard,this paper studies the collaborative optimization problem of berth allocation and yard storage from the point of the ships over a certain planning period.This...Considering the interaction between the berth and the yard,this paper studies the collaborative optimization problem of berth allocation and yard storage from the point of the ships over a certain planning period.This collaborative optimization problem is formulated as the integer programming,which aims at minimizing the total truck travel distance.And decision variables are the berthing positions for visiting ships and the storage positions for export containers.Meanwhile,this paper demonstrates the complexity of the problem in theory.And the hybrid tabu genetic algorithm is designed to solve the problem to obtain the optimal berth allocation position and export container storage position.For this algorithm,the rule is applied to generate the initial feasible solutions,and the crossover and mutation operation are simultaneously applied to optimize the initial solutions.Finally,this paper discusses two different scenes:the same berth scene and the same ship scene.The influence of two different scenes on truck travel distance is analyzed by different numerical examples.Numerical examples’results show that the collaborative optimization of berth allocation and yard storage can effectively shorten the truck travel distance and improve the efficiency of terminal operation,which provides the decision support for terminal operators.展开更多
This paper considers the ship routing optimization problem in a hub-and-spoke network. A routing optimization model for multi-type containerships with time deadlines is established, and the target is to minimize the t...This paper considers the ship routing optimization problem in a hub-and-spoke network. A routing optimization model for multi-type containerships with time deadlines is established, and the target is to minimize the total cost, which consists of the total travelling cost, total service cost and total waiting cost. The model is set up through an improved genetic algorithm. The study data are from the Pearl River Delta region of China, which include i hub port and 29 feeder ports and have a population of 30 million. Result shows that when the iteration time reaches 190, the total cost comes to 521 thousand yuan near the optimal value. There are 6 routes, including 3 containerships of 100 TEU, 2 containerships of 150 TEU and 1 containership of 200 TEU. At the same time, in the single-type containerships case, there are 7 routes, and when the iteration time reaches 120, the total cost comes to 573 thousand yuan, which is close to the optimal value. Comparing the two cases, it shows that the model for multi-type containerships with time deadlines is reasonable, and the algorithm is practicable. In the last, three factors, which may affect the total cost to carry out sensitivity analysis are chosen. It shows that time deadline, eontainership capacity and cargo handling capacity of each port have significant influence on the total cost. It is also shown that the total cost for multi-type containerships is always less than that for the single-type containerships.展开更多
文摘Considering the interaction between the berth and the yard,this paper studies the collaborative optimization problem of berth allocation and yard storage from the point of the ships over a certain planning period.This collaborative optimization problem is formulated as the integer programming,which aims at minimizing the total truck travel distance.And decision variables are the berthing positions for visiting ships and the storage positions for export containers.Meanwhile,this paper demonstrates the complexity of the problem in theory.And the hybrid tabu genetic algorithm is designed to solve the problem to obtain the optimal berth allocation position and export container storage position.For this algorithm,the rule is applied to generate the initial feasible solutions,and the crossover and mutation operation are simultaneously applied to optimize the initial solutions.Finally,this paper discusses two different scenes:the same berth scene and the same ship scene.The influence of two different scenes on truck travel distance is analyzed by different numerical examples.Numerical examples’results show that the collaborative optimization of berth allocation and yard storage can effectively shorten the truck travel distance and improve the efficiency of terminal operation,which provides the decision support for terminal operators.
基金supported by the National Nature Science Foundation of China(71072081)the Key Project of National Social Science Fund(14ZDB131)
文摘This paper considers the ship routing optimization problem in a hub-and-spoke network. A routing optimization model for multi-type containerships with time deadlines is established, and the target is to minimize the total cost, which consists of the total travelling cost, total service cost and total waiting cost. The model is set up through an improved genetic algorithm. The study data are from the Pearl River Delta region of China, which include i hub port and 29 feeder ports and have a population of 30 million. Result shows that when the iteration time reaches 190, the total cost comes to 521 thousand yuan near the optimal value. There are 6 routes, including 3 containerships of 100 TEU, 2 containerships of 150 TEU and 1 containership of 200 TEU. At the same time, in the single-type containerships case, there are 7 routes, and when the iteration time reaches 120, the total cost comes to 573 thousand yuan, which is close to the optimal value. Comparing the two cases, it shows that the model for multi-type containerships with time deadlines is reasonable, and the algorithm is practicable. In the last, three factors, which may affect the total cost to carry out sensitivity analysis are chosen. It shows that time deadline, eontainership capacity and cargo handling capacity of each port have significant influence on the total cost. It is also shown that the total cost for multi-type containerships is always less than that for the single-type containerships.
