Bilateral slot exchange and co-allocation for liner alliance carriers of containerized maritime logistics

With the maritime logistics technology evolving toward standardization and modernization, container liner shipping has become the most valued mode of transportation in the shipping industry. Liner carriers share resources in the alliance-based mode to achieve synergy. Specifically, slot exchange is a key and effective alliance-based means to enhance competitiveness and operational effectiveness. To this end, this article looks at how to optimize slot capacity allocation within a container liner alliance under the slot exchange mode in the containerized maritime logistics industry. First, we explained the slot exchange concept and its impact on the shipping business. Second, we identified the key factors that may affect slot allocation decisions. Then we established an optimal multi-objective slot exchange allocation model for liner alliances and solved the problem with the NSGA-II algorithm. Finally, taking the cooperation of two carriers on two trans-Pacific routes as an example, we used the model to establish the optimal slot exchange strategy for each carrier on the shipping alliance's routes to verify the practical application value of this model. The results showed that the model proposed in this article can help develop an optimal slot allocation plan, providing a scientific and effective tool for container liner alliances to formulate slot exchange and allocation strategies.     

Liner shipping network design with deadlines

It is crucial for a liner shipping company to design its container shipping network. Given a set of port-to-port container shipment demands with delivery deadlines, the liner shipping company aims to design itineraries of portcalls, deploy ships on these itineraries and determine how to transport containers with the deployed ships in order to maximize its total profit. In this paper we first demonstrate NP-hardness of this problem and subsequently formulate it as a mixed-integer non-linear non-convex programming model. A column generation based heuristic method is proposed for solving this problem. Numerical experiments for container shipping on the Asia–Europe trade lane show that the proposed solution algorithm is efficient to find good quality solutions.     

考虑恶劣天气的班轮多阶段重调度方法

受恶劣天气影响的船舶调度是一个非常复杂的优化问题,也是班轮公司重点关注的问题之一。为此,针对某航运网络上的一家班轮公司的所有营运船舶,以获知设计的多阶段重调度机制时段内最新预报的天气信息和这些船舶的实时位置为前提,重点考虑班轮船期表的限制并兼顾港口间航速变化和船舶容量等现实约束,构建了以固定计划期内所有船舶的航运总成本最小为优化目标的非线性数学模型,并设计了嵌入基因修复算子的改进遗传算法用于求解该模型。由此,可以给出集成租船直运、跨航线调船、反挂和货物中转等解决策略的最佳多阶段重调度方案。通过对大、中、小规模的算例进行实验,实验结果表明,可知与传统等待办法相比,多阶段重调度节约了总航运成本的15%以上,验证了所提模型和方案的有效性;与Cplex相比,改进遗传算法的运算效率大大提高,且偏差值均在5%以内,而与蚁群优化（ACO）算法、禁忌搜索（TS）算法、量子差分进化（QDE）算法相比,改进遗传算法能在有效时间内降低10%左右的成本,验证了算法的科学性。所提方法可为班轮公司的实际船舶调度提供参考。     

Competitive Liner Shipping Network Design

We present a solution method for the liner shipping network design problem which is a core strategic planning problem faced by container carriers. We propose the first practical algorithm which explicitly handles transshipment time limits for all demands. Individual sailing speeds at each service leg are used to balance sailing speed against operational costs, hence ensuring that the found network is competitive on both transit time and cost. We present a matheuristic for the problem where a MIP is used to select which ports should be inserted or removed on a route. Computational results are presented showing very promising results for realistic global liner shipping networks. Due to a number of algorithmic enhancements, the obtained solutions can be found within the same time frame as used by previous algorithms not handling time constraints. Furthermore, we present a sensitivity analysis on fluctuations in bunker price which confirms the applicability of the algorithm.     

Liner services network design and fleet deployment with empty container repositioning

Transportation demand of shipping container fluctuates due to the seasonality of international trade, thus, every 3–6 months, the liner company has to alter its current liner shipping service network, redeploy ships and design cargo routes with the objective of minimizing the total cost. To solve the problem, the paper presents a mixed integer linear program model. The proposed model incorporates several relevant constraints, such as weekly frequency, the transshipment of cargo between two or more service routes, and transport time. Extensive numerical experiments based on realistic date of Asia–Europe–Oceania shipping operations show that the proposed model can solve real-case problems efficiently by CPLEX. The results demonstrate that the model can reduce ship’s capacity consumption and raise ships’ capacity utilization.     

Mathematical modeling of yard template regeneration for multiple container terminals

As a tactical-level plan, the yard template determines the space allocation in a container terminal yard for all the arriving shipping liners. Generally speaking, the yard template will not change and it may last a matter of years. However, it has to be changed to response to the alteration of shipping liner. This paper investigates the problem of yard template regeneration for container port, which contains multiple container terminals. Firstly, the concept of yard template regeneration as well as the main influencing factors is proposed. Secondly, a multiple-objective mixed integer programming model is formulated which fully considering the minimum transportation cost, minimum template disturbance and maximum space utilization. Moreover, a case study is conducted to intuitively illustrate the regeneration problem of yard template. Finally, performance analysis and sensitivity analysis are performed to validate the effectiveness of the model.     

Multi-user symmetric cooperation based on nash bargaining solution in cooperative relay networks

This paper presents a symmetric cooperation strategy for cooperative relay networks with multiple users. The multi-user symmetric cooperation model and the relay selection algorithm are proposed. Then, the time slot allocation problem is cast into a bargaining problem, and the optimal time slot allocation solution is obtained by Nash bargaining solution (NBS). Moreover, we also consider the implementations of the cooperation strategy, i.e., the grouping and admission control algorithm. Simulation results show that users can obtain larger rates under the symmetric cooperation strategy than the non-cooperative case.     

An integrated optimization method for tactical-level planning in liner shipping with heterogeneous ship fleet and environmental considerations

The maritime transportation flows and container demand have been increasing over time, although the COVID-19 pandemic may slow down this trend for some time. One of the common strategies adopted by shipping lines to efficiently serve the existing customers is the deployment of large ships. The current practice in the liner shipping industry is to deploy a combination of ships of different types with different carrying capacities (i.e., heterogeneous fleet), especially at the routes with a significant demand. However, heterogeneous fleets of ships have been investigated by a very few studies addressing the tactical liner shipping decisions (i.e., determination of service frequency, ship fleet deployment, optimization of ship sailing speed, and design of ship schedules). Moreover, limited research efforts have been carried out to simultaneously capture all the major tactical liner shipping decisions using a single solution methodology. Therefore, this study proposes an integrated optimization model that addresses all the major tactical liner shipping decisions and allows the deployment of a heterogeneous ship fleet at each route, considering emissions generated throughout liner shipping operations. The model’s objective maximizes the total turnaround profit generated from liner shipping operations. A decomposition-based heuristic algorithm is presented in this study to solve the model proposed and efficiently tackle large-size problem instances. Numerical experiments, carried out for a number of real-world liner shipping routes, demonstrate the effectiveness of the proposed methodology. A set of managerial insights, obtained from the proposed methodology, are also provided.     

Schedule design for sustainable container supply chain networks with port time windows

This paper studies a practical liner shipping schedule design problem with port time windows for container supply chain networks. A mixed-integer nonlinear non-convex model that incorporates the availability of ports is proposed to minimize the sum of ship cost and fuel cost (and thereby pollutant emission). In view of the structure of the problem, we reformulate it as an integer linear optimization model and propose an iterative optimization approach. The proposed solution method is applied to two liner networks operated by a global shipping line.     

考虑多约束的混合流水车间MOJ 调度

考虑晶圆加工过程中的多品种和与次序相关的换模时间约束,以系统总完工时间最小为优化目标,建立混合流水车间MOJ调度模型.在此基础上,提出了基于作业-产品-机器三层析取网络流的列生成算法.为进一步改善列生成算法存在的尾效应,将基于次梯度优化的拉格朗日松弛算法嵌入列生成算法框架中,构建了采用双重迭代的改进型列生成(MCG)算法.最后,通过理论分析和仿真实验表明了MCG算法是有效、可行的.     

A study on bunker fuel management for the shipping liner services

In this paper, we consider a bunker fuel management strategy study for a single shipping liner service. The bunker fuel management strategy includes three components: bunkering ports selection (where to bunker), bunkering amounts determination (how much to bunker) and ship speeds adjustment (how to adjust the ship speeds along the service route). As these three components are interrelated, it is necessary to optimize them jointly in order to obtain an optimal bunker fuel management strategy for a single shipping liner service. As an appropriate model representing the relationship between bunker fuel consumption rate and ship speed is important in the bunker fuel management strategy, we first study in detail this empirical relationship. We find that the relationship can be different for different sizes of containerships and provide an empirical model to express this relationship for different sizes of containerships based on real data obtained from a shipping company. We further highlight the importance of using the appropriate consumption rate model in the bunker fuel management strategy as using a wrong or aggregated model can result in inferior or suboptimal strategies. We then develop a planning level model to determine the optimal bunker fuel management strategy, i.e. optimal bunkering ports, bunkering amounts and ship speeds, so as to minimize total bunker fuel related cost for a single shipping liner service. Based on the optimization model, we study the effects of port arrival time windows, bunker fuel prices, ship bunker fuel capacity and skipping port options on the bunker fuel management strategy of a single shipping liner service. We finally provide some insights obtained from two case studies.     

跨区域远洋航线空集装箱动态调运优化模型

由于海运业受世界经济不景气的影响,班轮企业竞争日益加剧。尽可能地降低营运成本是班轮企业生存和发展的关键因素。提出了跨区域远洋空集装箱动态调运优化模型（ECR-RDM）,该模型一方面针对传统模型（ECR-TM）基于港口间点到点空箱调运策略的缺陷,采用了基于港口集合到集合的空箱调运策略。另一方面,不同于传统模型解决空箱调运的静态分配特征,提出的模型可以根据实时需要动态分配空箱,一定程度上减少了由于调运计划和实际业务需求不同步性产生的各项成本。通过抽取实际业务中可能发生的六种情况,依次进行分析比较,验证了文中提出模型的有效性和可行性。同时,通过分析在可能的六种情况下租赁成本、存储成本、装卸成本在总调运成本中所占的比例,为班轮企业制定高效的运营策略提供决策依据。     

钢铁企业全流程物流优化问题的建模及分支——定价算法

研究了钢铁企业的全流程物流优化问题, 该问题在确保全流程各个工序机组产能和库存能力限制以及满足客户需求的前提下, 决策炼钢、连铸、热轧及冷轧工序间的物料流向和流量, 最小化物流成本、产能损失及库存费用. 为该问题建立了混合整数规划(Mixed integer programming, MIP)模型. 在问题求解中, 首先对MIP模型进行了Dantzig-Wolfe分解, 得到一个结构相对简单但列变量数目非常多的主问题和四个描述列向量空间的子问题. 然后, 从一个包含部分列变量的限制主问题出发, 通过子问题和主问题之间的迭代来获取主问题线性松弛的最优解. 最后, 将列生成同分支—定界相结合, 即分支—定价算法, 以获取原问题的整数最优解. 对某钢铁企业的实际生产数据扩展的随机算例进行仿真实验, 结果显示所提出的算法能够在合理计算时间内获得最优解或次优解.     

Fast Distributed Demand Response Algorithm in Smart Grid

This paper proposes a fast distributed demand response (DR) algorithm for future smart grid based on primaldual interior method and Gaussian belief propagation (GaBP) solver. At the beginning of each time slot, each end-user/energysupplier exchanges limited rounds of messages that are not private with its neighbors, and computes the amount of energy consumption/generation locally. The proposed demand response algorithm converges rapidly to a consumption/generation decision that yields the optimal social welfare when the demands of endusers are low. When the demands are high, each end-user/energysupplier estimates its energy consumption/generation quickly such that a sub-optimal social welfare is achieved and the power system is ensured to operate within its capacity constraints. The impact of distributed computation errors on the proposed algorithm is analyzed theoretically. The simulation results show a good performance of the proposed algorithm.      

基于头脑风暴算法的电动货车路径优化问题

针对电动货车路径优化问题,应用物流网络以及电动货车电量消耗等方面的知识,研究了电动货车的智能调度方法,构建了带时间窗的电动货车路径优化模型(electric vehicle routing problem with time window,EVRPTW)。该模型考虑了耗电量与电动货车行驶速度、载重量之间的关系,客户满意度与软时间窗之间的关系。同时,引入了计算机智能算法,充分利用了遗传算法、头脑风暴算法等优化算法的智能化特征,有效提高了电动货车的配送效率。仿真结果表明:该模型运用头脑风暴算法的最优值精确度和收敛速度都优于遗传算法,可以有效解决EVRPTW问题。所提出的模型和算法能明显提高配送中心的配送效率,节省充电成本,提高顾客满意度。针对配送中心电动货车运营调度管理的特点,借助计算机技术以及自动控制技术,进一步提高了电动货车的配送效率,为物流网络系统的智能化调度提供技术准备。     

风力发电与电动汽车充放电协同优化调度策略

大规模电动汽车无序充电以及风力发电在电网中的渗透率不断提高,给电力系统带来安全经济运行问题。在考虑电动汽车电池容量约束、充放电功率约束以及24 h的电动汽车运行行为特性基础上,建立了风力发电及电动汽车负荷平抑、降低电动汽车充放电费用和负荷峰谷差率的多目标协调优化调度模型;采用传统遗传算法和自适应非线性遗传算法对所建模型进行求解。仿真结果验证了模型的合理性以及算法的正确性。     

Avocados crossing borders: The problem of runaway objects and the solution of a shipping information pipeline for improving international trade

This paper investigates the case of shipments of containers with avocados from farmers in Africa to grocery store shelves in the European Union. We find 3 predominant challenges to containerized shipping that effectively become trade barriers: international trade cost, lead time uncertainty, and security risks. We use activity theory to describe, understand, and analyze the shipping activity in the international trade ecosystem with focus on physical objects and their related information. We find that the shipment becomes problematic and can be characterized as a runaway object in the heterogeneous and multiple organizational setting of international trade. Our analysis of shipping reveals (1) inefficient collaboration across loosely coupled activity systems and (2) fragmented information infrastructures. We propose the solution of Shipping Information Pipeline, a shared information infrastructure, thus facilitating collaboration in containerized shipping and contributing to lowering trade barriers. Shipping Information Pipeline can significantly improve containerized shipping resulting in estimated potential benefits of up to 4.7% growth in global GDP.     

A branch-and-price algorithm to solve the molten iron allocation problem in iron and steel industry

The molten iron allocation problem (MIAP) is to allocate molten iron from blast furnaces to steel-making furnaces. The allocation needs to observe the release times of the molten iron defined by the draining plan of the blast furnaces and the transport time between the iron-making and steel-making stages. Time window constraints for processing the molten iron must be satisfied to avoid freezing. The objective is to find a schedule with minimum total weighted completion time. This objective reflects the practical consideration of improving steel-making efficiency and reducing operation cost caused by the need for reheating. Such a problem can be viewed as a parallel machine scheduling problem with time windows which is known to be NP-hard. In this paper, we first formulate the molten iron allocation problem as an integer programming model and then reformulate it as a set partitioning model by applying the Dantzig–Wolfe decomposition. We solve the problem using a column generation-based branch-and-price algorithm. Since the subproblem of column generation is still NP-hard, we propose a state-space relaxation-based dynamic programming algorithm for the subproblem. Computational experiments demonstrate that the proposed algorithm is capable of solving problems with up to 100 jobs to optimality within a reasonable computation time.     

微电网系统的分布式优化下垂控制

针对微电网系统运行成本最优化问题,提出一种分布式优化下垂控制策略.首先,基于一致性理论,给出了一种分布式经济调度算法.采用矩阵摄动理论,分析了经济调度算法的收敛特性.其次,基于分布式优化调度解,设计一种新的分布式优化下垂控制器.在满足供需平衡以及各个发电单元运行约束的条件下,控制策略使得微电网系统运行成本最低.同时,提出的控制策略能够保证孤岛微电网的频率稳定在额定值.最后,通过仿真实例,验证了分布式优化下垂控制策略的有效性.     

三层物流网络选址-路径优化及混合启发式算法研究*

为同时解决转运、分配、选址和车辆路径问题,在考虑车辆载重和行驶距离约束,配送中心处理能力约束的基础上,构建了一个多产品三层物流网络选址-路径模型,以总成本最小为目标,提出一种基于贪婪随机自适应搜索算法和里程节约算法的混合启发式算法,给出了该算法的步骤和伪代码。实验结果表明该算法具有可行性,并且与其他算法比较而言,算法具有高效性。