The optimization of ship scheduling in water-land transshipment plays a crucial part in enhancing transportation efficiency and alleviating traffic congestion on inland waterways, particularly when the service capacity of locks is insufficient. This study focuses on the ship scheduling problem in an anchorage-to-quay channel, where the navigation of ships is influenced by the water discharge during flood seasons. A new mixed-integer linear programming (MILP) model is formulated for this problem, in which the interconnected decision of ships’ navigation and berthing activities, the variation of water discharge in the waterway channel, and the change of navigation scenarios (i.e., normal or flood impact) are explicitly taken into account. Then a multi-population genetic algorithm (MPGA) is applied to solve this model. Numerical experiments conducted for the Three Gorges Dam (TGD) demonstrated that the proposed heuristic method can tackle the ship scheduling problem within a reasonable time, which is also effective in assisting ships to match acceptable water discharge time window by slightly adjusting the departure time of ships at the anchorage or quay. Furthermore, the proposed method can ensure the navigational safety of ships and improve the efficiency of ship transportation in different scenarios, and quantitatively evaluate the water discharge impact.

Motivated by the operational scenarios of lock scheduling, we propose a serial-lock chain navigation problem (SLCNP) modeled on the Three Gorges-Gezhouba Dam (TGGD) for the first time. Ship grouping, synchronized moving, and grouped waiting operations are integrated into the ship navigation process. A mixed integer programming (MIP) model that incorporates real-world constraints such as ship priority, service fairness, traffic flow equilibrium, and phased ship placement is presented to optimize ship throughput and ship stay time. To solve the SLCNP, a sort-pick strategy-based swarm intelligence algorithm (SPSSIA) framework is developed that integrates the characteristics of SLCNP through a hybrid multi-section encoding method and a two-stage heuristic decoding approach. A swarm intelligence evolution mechanism is used to improve the search ability and robustness of the framework. Several instances are generated based on real data to verify the correctness and effectiveness of the model and algorithm. Computational results demonstrate the applicability and effectiveness of the proposed SPSSIA. Further analysis of the experimental results indicates that the key impact factors significantly influence the navigational performance of the TGGD system. The results of this study will provide practical guidance for the operational processes of inland river hubs with comparable characteristics.

There is growing interest in the lock group co-scheduling research because of serious capacity imbalance between two dams at Three Gorges-Gezhou Dams Hub (TGDH). However, most current studies ignore the impact of ship lift and approach channel on navigation efficiency, and the energy consumption from vessels on ecological environment. Encouraged by this, we investigate an energy-efficient lock group co-scheduling problem at the TGDH with the consideration of ship lift as well as approach channel. A new multi-objective model for the problem is proposed, aiming to simultaneously optimize the average area utilization of all locks, average tardiness of vessels and total energy consumption of vessels. A collaborative adaptive multi-objective algorithm (CAMOA) is well-designed to solve the studied problem. The CAMOA makes use of a well-tailored two-layer encoding scheme and a three-stage group-shift decoding approach to represent and decode each solution. Next, an adaptive adjustment search strategy based on step control factor is periodically triggered to reinforce local exploitation capability, where a novel fuzzy correlation entropy analysis is coupled to evaluate the neighborhood solutions. Extensive simulation experiments are implemented according to the real-world data from the TGDH. The statistical results demonstrate that the proposed CAMOA is efficient and reliable in solving the studied problem. This work is very significant for TGDH to improve the passing efficiency and reduce the energy consumption.

Channels and locks are crucial resources for ships of inland waterways. This paper addresses the ship scheduling problem based on channel-lock coordination, where ships entering the channel are affected by water discharge during flood season. A ship scheduling optimization model is formulated to minimize the total waiting time of ships at the anchorage. The model takes into account the decision-making of the departure time of ships, the change of water discharge in different scenarios, and the coordinated allocation of channels and locks. A dynamic multi-population particle swarm optimization algorithm with recombined learning and hybrid mutation (DMPSO-RH) is proposed to solve the model of ship scheduling. Numerical experiments conducted for the Three Gorges Dam (TGD) demonstrate that the DMPSO-RH can obtain nearly optimal solutions for practical large-sized ship scheduling problems within a reasonable time. By optimizing the departure time and sequence of ships, the scheduling scheme generated by the DMPSO-RH can effectively match the channel operation time and the lockage starting time, which helps to enhance the coordination of channels and locks at the TGD in different scenarios. Due to these improvements, the total waiting time of ships in the two scenarios is reduced by 29.08% and 28.59%, respectively, and the carbon emissions of ships are reduced accordingly. This approach can avoid navigation risks and improve the efficiency of ship scheduling in flood season. Moreover, the result of this study is very useful to reduce the waiting time and improve the environmental pollution of ships at the TGD.

Since the demands of waterway transport on the Yangzi River have been growing in recent years, traffic congestion at Three Gorges Dam (TGD) has become a very serious issue, which leads to long waiting time as well as environmental pollution. To improve the efficiency of the ship traffic scheduling, this paper investigates an approach channel and lock co-scheduling problem of the TGD on the Yangzi River. A new mathematical model is presented to optimize the lock chamber utilization rate, average waiting time and total energy consumption of ships, simultaneously. To solve this problem, a multi-objective metaheuristic algorithm (MOMA) based on fuzzy correlation entropy is proposed. In the algorithm, with a ship sequence encoding scheme, a pre-grouping panning approach is firstly designed for decoding. Then, a fitness evaluation mechanism using fuzzy correlation entropy is adopted to assess the solutions. Finally, an adaptive local reinforcement search strategy is introduced to improve local intensification ability. Various simulation experiments are carried out based on the real historical data at TGD. Computational results demonstrate the applicability and effectiveness of proposed MOMA. The result of this study is very useful for TGD to improve the ship traffic efficiency and save energy.

This paper deals with a reentrant hybrid flow shop problem with sequence-dependent setup time and limited buffers where there are multiple unrelated parallel machines at each stage. A mathematical model with the minimization of total weighted completion time is constructed for this problem. Considering the complexity of the problem at hand, an effective cooperative adaptive genetic algorithm (CAGA) is proposed. In the algorithm, a dual chain coding scheme and a staged-hierarchical decoding approach are, respectively, designed to encode and decode each solution. Six dispatch heuristics and a dynamic adjustment method are introduced to define initial population. To balance the exploration and exploitation abilities, three effective operations are implemented: (1) two new crossover and mutation operators with collaborative mechanism are imposed on genetic algorithm; (2) an adaptive adjustment strategy is introduced to re-optimize better solutions after mutation operations, where ant colony search algorithm and modified greedy heuristic are intelligently switched; (3) a reset strategy with dynamic variable step strategy is embedded to re-generate some non-improved solutions. A Taguchi method of design of experiment is adopted to calibrate the parameter values in the presented algorithm. Comparison experiments are executed on test instances with different scale problems. Computational results show that the proposed CAGA is more effective and efficient than several well-known algorithms in solving the studied problem.

This paper investigates a multi-objective green co-scheduling problem of ship lift and ship lock (GCP-SL&SL) at the Three Gorges Cascade Hub (TGCH). A mathematical model of GCP-SL&SL with objectives of the average utilizations rate of the lock chamber, average waiting time and total energy consumption of vessels, is proposed by separating it into three sub-problems: the facility assignment, lockage assignment and lockage operation scheduling. To solve this problem, a discrete multi-objective artificial bee colony (DMOABC) algorithm is developed. Within the DMOABC, a two-dimensional matrix encoding scheme is designed to encode and a group right-shift decoding scheme is specifically proposed to decode each food source. Then, a novel fitness evaluation mechanism based on fuzzy relative entropy is introduced to hand this multi-objective problem. Next, the food sources are improved from three aspects: (1) the employed bee phase uses new evolutionary operators for fast local search; (2) the onlooker bee phase adopts a modified tabu search for strong global search; (3) the scout bee phase embeds chemical reaction optimization for disturbing population. Finally, extensive experiments are conducted with the real data from historical traffic at TGCH. The results demonstrate our proposed algorithm is significantly better at solving the GCP-SL&SL than other five well-known multi-objective algorithms. The effect analysis under different scenarios indicates that the average waiting time of vessels at the dam is greatly reduced because of considering the synchronous moving process.

经过6个五年计划期的建设发展,湖南省重点推进的湘江航道建设和航电枢纽滚动开发示范作用明显,湘江树立了干流航运品牌,同时成为了湖南省水运大动脉和南北综合运输大通道.通过系统总结湘江干流航运建设历程,展示航运梯级、主要港口及航道建设成果,归纳、提炼湘江干流航运品牌建设理念,为畅通、高效、平安、绿色的现代化内河水运体系建设提供经验参考.

As an important project on the golden waterway of the Yangtze River in China, the Three Gorges–Gezhouba Dams (TGGD) plays a pivotal role in the construction of the Yangtze River Economic Belt. To improve the efficiency and safety of ship traffic, some novel navigation regulations have been implemented that change the TGGD operation obviously. For example, a piecewise control strategy proposed in the regulations is applied to control the traffic flow of ships under a sectional manner. With the implementation of these regulations, how to understand the dynamic effects of new changes on TGGD has been an important problem. The purpose of this work is to evaluate the navigation performance of the TGGD via a data- and event-driven hybrid simulation model developed by multi-agent and discrete-event modeling theories. The model simulates the three significant navigable scenarios inherent in the actual operating environment: dry season, wet season, and flood season, reflecting the real situations. The input data come from the statistical analysis of the actual navigation data provided by the Three Gorges Navigation Administration. The validity and reliability of the model are verified by comparing the output results with actual data. Moreover, a set of test experiments are designed to explore the TGGD navigation limit and analyze the key factors that restrict the navigation capacity of the TGGD system. The work is expected to provide a certain decision support for the future cooperative scheduling optimization of the TGGD.

This paper addresses a flexible flow shop scheduling problem considering limited buffers and step-deteriorating jobs, where there are multiple non-identical parallel machines. A mixed integer programming model is proposed, with the criterion of minimizing the makespan and total tardiness simultaneously. To handle this problem, an effective hybrid meta-heuristic algorithm, named GVNSA, is developed based on genetic algorithm (GA), variable neighborhood search (VNS) and simulated annealing (SA). In the algorithm, with a two-dimensional matrix encoding scheme, the NEH (Nawaz–Enscore–Ham) heuristic and bottleneck elimination method are implemented to determine the initial population. A three-level rolling translation approach is designed for decoding. To balance the exploration and exploitation abilities, three effective steps are executed: 1) partial matching crossover and mutation strategy based on multiple neighborhood search structures are imposed on the GA operators; 2) a VNS with SA is introduced to re-optimize some individuals from GA, where four neighborhood structures are constructed; 3) a modified CDS (Campbell–Dudek–Smith) heuristic is embedded to disturb population in the mid-iteration. Numerical experiments are carried out on test problems with different scales. Computational results demonstrate that the proposed GVNSA can obtain higher quality solutions in comparison with other heuristics and meta-heuristics existing in literature.

针对湘江渠化河段大花滩连续弯道滩险航道整治措施进行研究.采用非结构化网格,建立工程河段二维水流数学模型和船舶操纵运动数学模型.验证原型实测水位验证模型的可靠性后,计算得到了不同流量情况下工程河段的航道水深、流场以及船模操纵的舵角、漂角、最小航速等主要参数.结果表明:工程河段内不实施切嘴及整治建筑物也可通过优化航线、拓宽航宽并结合适当的疏浚、护岸工程措施满足通航标准要求.

The passenger-cargo Roll on/Roll off ship stowage (PRSS) is the core step of passenger-cargo Roll on/Roll off (RoRo) transportation. The layout of vehicles in the cabin is directly related to the space utilization of the cabin and the efficiency of stowage operations, which in turn affects the economic benefits of the port. In this paper, we address the PRSS problem in the context of passenger-cargo RoRo transportation in the Qiongzhou Strait of China. By focusing on the utilization ratio of the cabin area, the PRSS problem can be viewed as a special version of a two-dimensional knapsack packing (2D-KP) problem with additional constraints, such as two-phase, complex rotation and safe navigation constraints. Then we present a mixed integer linear programming (MILP) mathematical model and an algorithm framework to tackle the PRSS problem. In the algorithm framework, a novel multi-phase heuristic stowage method is proposed to improve the current manual stowage decision-making state which completely depends on operational experience. Finally, several instances are generated based on the realistic date of Qiongzhou Strait to verify the effectiveness of the model and stowage method. Computational results show that the proposed model and stowage method are well suited to solve the PRSS problem and the algorithm framework has a strong robustness in large-scale application experiments.

针对株洲航电枢纽坝下渌口、辰洲、错石和萝卜洲四个滩险,开展株洲与长沙枢纽共同影响下的坝间航道整治数值分析工作.采用非结构化网格,建立了株洲枢纽下游引航道-株洲一桥航道整治工程所在河段二维水流数学模型.采用实测水文数据,验证了模型的可靠性.运用数学模型分别进行工程效果、渌口滩丁坝拆除方案影响分析工作.

针对枢纽上游渠化河段取水口对通航水流条件影响问题,文章以某临湘江取水口工程所在河道为例开展研究.基于浅水方程建立了湘江浯溪枢纽上游河段的平面二维水流数学模型,研究不同取水工况对工程河段水位、流态的影响.研究表明,取水过程仅对取水头部局部范围内水流条件有影响,且对航道水面比降、纵向流速及横向流速影响均较小,总体上对库区航道通航水流条件影响甚微,穿越航道取水方式可行.研究可为类似穿越航道的取水口河段通航影响分析提供参考.

大源渡航电枢纽现存的一线船闸已不能满足航运需求,需在旁侧建立二线船闸.一线船闸的启闭机液压系统存在压力损失大、 动态响应慢、 效率低、 自动化程度有限等问题,对二线船闸启闭机液压系统进行改进设计和研究,达到效率高、 动态响应高、 节能、 安全和全自动控制.在深入研究和试验的基础上,二线船闸的液压控制系统采用泵控式,且优化人字门的同步控制策略,满足运动工况的性能要求.通过模拟试验验证,证明了设计的合理性和创新性.

大源渡航电枢纽拟增建鱼道,受枢纽总平面布置条件限制,鱼道进口如果布置在电站尾水,则施工难度和投资均较大,存在严重安全隐患.为既确保安全、 节省投资,又满足过鱼要求,采用SMS-RMA2模型建立了平面二维水动力数学模型,模拟得出枢纽坝轴线下游一定范围内多种不同工况下的流场图,为在坝址所处微弯分汊河段找到合适的鱼道进口位置提供了可靠的参考依据.为提高过鱼效果,建议在鱼道进口上游侧设置导鱼电栅等拦鱼系统和喷淋水声、 灯光等诱鱼系统,帮助鱼类及早发现鱼道入口.

In order to improve the space utilization of the yard and enhance the working efficiency of general cargo terminal, the paper analyzes the remaining storage allocation problem in general cargo yard by referring to two-dimensional rectangular layout theory. The model of the remaining storage allocation is established with the aim of maximizing the space utilization of the yard, and three different heuristic algorithms are used to solve the model respectively in the case of sufficient storages and insufficient storages of the yard. The results show that the BL algorithm and the BF algorithm can effectively optimize the problem. In the case of sufficient storages of the yard, the remaining storage allocation scheme based on the BL algorithm that about 4% of the available area of the yard can be saved compared to the BF algorithm and about 14% of the area can be saved compared to the lowest horizontal line algorithm. In the other case, the scheme based on the BF algorithm that about 7% of the available area of the yard can be saved compared to the BL algorithm and about 10% of the area can be saved compared to the lowest horizontal line algorithm.

湖南省水运资源丰富，通过分析全省14个地州市及124个县市区的水系连通条件及航道发展现状，结合“十三五”水运建设规划提出的建设重点以及自下游向上游、自干流向支流发展的建设方案，对全省“十三五”期末水运发展前景进行展望：湘江全面实现中远期规划目标，沅水基本实现中远期规划目标；14个地州市中，除张家界市临澧水河段仍区间通航外，其余13个地州市可以实现直接或通过一级支流与四水和洞庭湖骨干航道的有效连通，从而大大延伸水运通达和覆盖范围，全面促进全省经济发展。

针对湘江长沙综合枢纽右汊砂砾石闸基,为满足地基承载力及沉降要求,选择振动沉管碎石桩处理方案,通过介绍设计过程、分析成桩试验及复合地基载荷试验结果,为碎石桩在稍~中密砂砾石地基处理中的应用提供了设计、施工经验,可供类似工程参考。

The eccentric compression member with circular section is one kind of reinforced concrete structures that has been widely used and the calculation on bearing capacity of R.C.members with circular section is much more complicated than those with the rectangular cross-section.To simplify the calculation,corresponding assumptions have been given by various existing standards.Based on the analysis and comparison of the process of simplification as well as the contents of various calculation methods,analysis and comparison have been done to the precision of the calculation results of certain examples by using various calculation methods and the conclusions have been given.The design and calculation of bearing capacity of R.C.member with circular section in a more convenient and efficient way are would contributed to.