Application of a combined fuzzy multiple criteria decision making and optimization programming model to the container transportation demand split

The container transportation demand split is one of the most important decision issues for government transportation departments and port organizations. In previous studies, many researchers assumed that the shipping carrier would aim to minimize the total operation cost by selecting an appropriate port as the most favorable one to call, and the shipper would aim to minimize the inland freight cost by selecting the nearest port as the most favorable one to import and export international trade containers. Thus, a number of mathematical programming models have been developed. But in practice, the shipping carrier not only aims to minimize the total operation cost but also takes into account other criteria such as the volume of containers and port facility conditions when choosing an appropriate port as the most favorable one to call. The shipper not only aims to minimize the inland freight cost but also takes into account the frequency of ship callings when choosing an appropriate port as the most favorable one to import and export international trade containers.Thus, the purpose of this paper is to formulate a combined fuzzy multiple criteria decision making and optimization programming model for solving the container transportation demand split problem. There are two stages in this combined model: in stage one, we first compute the container transportation demand split rate by using fuzzy multiple criteria decision making (MCDM) method; whereas in stage two, an optimization mathematical programming network model is proposed for determining the inland origin destination (O-D) of import/export containers. The utilization of the proposed model is demonstrated with a case of Taiwanese ports. The results show that the proposed combined fuzzy MCDM and optimization programming model can be used to explain the container transportation demand split practice.     

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。     

基于($D,U$)控制策略的港口群空箱存储与调运联合优化

针对区域港口群内陆公共腹地的空箱供需状况,构建多港口、多周期空箱存储与调运联合优化混合整数规划模型,利用马尔科夫决策过程与动态规划相结合的方法,在(D,U)库存控制策略下对港口群内各港口的空箱库存保有量区间进行动态优化,以此为基础对港口群公共腹地和各港口间的空箱调运方案进行优化,并以辽宁沿海港口群-----东北腹地为对象进行实证分析.实验结果表明,(D,U)控制策略下的空箱调运能够为船公司节省15.22%的总成本.选取公共腹地数量、公共腹地和港口空箱需求量、单位租箱成本以及单位库存成本进行灵敏度分析,进而验证(D,U)控制策略能够削弱船公司在外界环境发生变化时受到的影响.     

集装箱海运空箱分派随机规划模型研究*

通过对海运集装箱空箱分派过程的仔细分析,在考虑需求不确定性的基础上引入了空箱运输能力的不确定性这一重要因素,建立了同时考虑供需平衡约束以及需求和空箱运输能力不确定性的空箱分派随机规划模型,并应用机会约束规划方法对模型求解.最后通过数值仿真,揭示了运输成本、租箱成本和存储成本等参数和空箱运输能力的不确定性对集装箱空箱分派策略的影响机制.     

A recursive model for static empty container allocation

Backlogged empty containers have gradually turned into a serious burden to shipping networks. Empty container allocation has become an urgent settlement issue for the container shipping industry on a global scale. Therefore, this paper proposes an improved immune algorithm based recursive model for optimizing static empty container allocation which integrates with the global maritime container shipping network. This model minimizes the operating and capital costs during container shipping considering 0–1 mixed-integer programming. So an immune algorithm procedure based on a special twodimensional chromosome encoding is proposed. Finally, computational experiments are performed to optimize a 10-port static empty container shipping system. The results indicate that the proposed recursive model for static empty container allocation is effective in making an optimal strategy for empty container allocation.     

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.     

Maritime repositioning of empty containers under uncertain port disruptions

This paper addresses the problem of repositioning empty containers in maritime networks under possible port disruptions. Since drastically different futures may occur, the decision making process for dealing with this problem cannot ignore the uncertain nature of its parameters. In this paper, we consider the uncertainty of relevant problem data by a stochastic programming approach, in which different scenarios are included in a multi-scenario optimization model and linked by non-anticipativity conditions. Numerical experiments show that the multi-scenario solutions provide a hedge against uncertainty when compared to deterministic decisions and exhibit some forms of robustness, which mitigate the risks of not meeting empty container demand.     

考虑港口拥堵因素的沿海海运网络优化

沿海运输权制度是沿海运输是否保留给本国船舶或者向外国籍船舶开放的制度。港口拥堵主要发生在海运网络的枢纽港上。通过考虑沿海运输权和港口拥堵对轴辐式海运网络加以优化,以海运网络内货物运输总成本最小化为目标函数,构建一个小规模整数规划模型。从欧亚航线覆盖的主要地区中选取10个港口组成海运网络进行算例分析,并使用CPLEX软件进行求解,研究结果表明,通过考虑枢纽港间货物运输的规模经济效应和产生的拥堵成本,可合理地确定枢纽港的位置;若允许沿海捎带,外资航运企业将会改变货物中转的港口。     

Empty container repositioning strategy in intermodal transport with demand switching

In this paper, we study the empty container inventory repositioning problem with customer demand switching in intermodal transport. The objective of this article is to solve the empty container repositioning problem by contract coordination theory, and to improve the coordination of empty container management and the profit of each participant. We consider an intermodal transport system composed of the rail firm and the liner firm. First, we have considered the situation of no cooperation between the dry port and the seaport, and established a model where there is only the customer demand switching without the occurrence of empty container repositioning. Next, we consider the cooperation between the dry port and the seaport in the decentralized model and the centralized model, and set up the empty container repositioning models from the seaport to the dry port respectively. We analyse the optimal inventory level for the dry port and the seaport under different models, and the effect of the repositioning price on the optimal inventory level. We then apply the contract coordination theory to the empty container inventory repositioning problem. We propose an inventory coordination strategy based on a revenue sharing contract and coordinate the intermodal transport system by choosing the appropriate contract parameters. The results of the study show that under the guidance of the seaport, the revenue sharing contract can achieve a win-win situation for the dry port and the seaport.     

Exact and approximate solutions of the container ship stowage problem

This paper deals with a stowage plan for containers in a container ship. Containers on board a container ship are placed in stacks, located in many bays. Since the access to the containers is only from the top of the stack, a common situation is that contianers designated for port J must be unloaded and reloaded at port I (before J) in order to access containers below them, designated for port I. This operation is called “shifting”. A container ship calling many ports, may encounter a large number of shifting operations, some of which can be avoided by efficient stowage planning. In general, the stowage plan must also take into account stability and strength requirements, as well as several other constraints on the placement of containers. In this paper we deal with stowage planning in order to minimize the number of shiftings, without considering stability constraints. First, a 0–1 binary linear programming formulating is presented that can find the optimal solution for stowage in a single rectangular bay of a vessel calling a given number of ports, assuming that the number of constainers to ship is known in advance. This model was successfully implemented using the GAMS software system. It was found, however, that finding the optimal solution using this model is quite limited, because of the large number of binary variables needed for the formulation. For this reason, several alternative heuristic algorithms were developed. The one presented here is based on a “reduced” transportation matrix. Containers with the same source and destination ports are stowed in full stacks as much as possible, and only the remaining containers are allocated by the binary linear programming model. This approach often allows the stowage planning of a much larger number of containers than using the exact formulation.     

集装箱港口集群下多港口多泊位联合调度方法

目前对港口和泊位的调度研究尚停留在单港口多泊位,而在集装箱港口集群条件下对多港口多泊位实行船舶的联合调度可以充分实现港口资源的优化配置。为了充分利用港口资源,实现船舶在港时间最短,且服从船公司运输成本最低的目的,建立了集装箱港口集群下多港口多泊位联合调度的多目标非线性决策模型,并按照模型决策空间所具有的特殊条件,设计了改进的遗传启发式算法,结果表明船舶靠泊成本大幅降低,港口利用率大幅提高。通过大量真实和随机算例验证了算法的有效性和稳定性,证明了模型和算法实用有效。     

Positioning empty containers under dependent demand process

Owing to trade imbalance, shipping companies position empty containers between ports or depots periodically. The most difficult problem for positioning is that it is not possible to know the exact amounts of empty containers required in the future. The paper deals with the problem of positioning empty containers in a port area with multiple depots. Customer demands and returning containers in depots per unit time period are assumed to be serially-correlated and dependent random variables. Three options are considered to prepare the required extent of positioning: positioning from other overseas ports, inland positioning between depots, and leasing. The policies for empty-container management consist of three parts as follows: a coordinated, (s, S) inventory policy for positioning from other ports, (r_i, R_i) policy for inland positioning between depots; and a simple leasing policy with zero lead-time. For inland positioning policy, four heuristic methods are proposed to reposition empty containers between depots. The objective is to obtain optimal policies corresponding to different methods of inland positioning in order to minimize the expected total costs. A genetic-based optimization procedure is developed to find the optimal parameters (s, S) and (r_i, R_i). Some numerical examples and sensitivity analyses are given to demonstrate the results.     

Collaborative mechanisms for berth allocation

This paper proposes two collaborative mechanisms between container shipping lines and port operators to facilitate port operators to make proper berth allocation decisions. In the first mechanism, assuming no transshipment, a shipping line needs to provide the port operator with the utilities associated with the start operation days of each liner route. The total utilities for all start operation days must be 0. A higher bunker and inventory cost for the shipping line means a lower utility. The port operator compensates the shipping line if its ship is scheduled on a day with negative utility and charges additional fees if the ship is scheduled on a day with positive utility. The second mechanism accounts for the utilities related to the inventory cost of transshipment containers. These two mechanisms ensure that shipping lines have no incentive to overstate or undervalue the utilities. The utilities estimated by shipping lines are much more accurate than those estimated by port operators. Hence, models for the tactical berth allocation problem incorporating the utilities provided by shipping lines lead to more efficient and equitable berth allocation plans. The utilities provided by shipping lines can also guide the decisions on operational berth allocation.     

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-objective reliability-redundancy allocation problem using particle swarm optimization

This paper considers the multi-objective reliability redundancy allocation problem of a series system where the reliability of the system and the corresponding designing cost are considered as two different objectives. Due to non-stochastic uncertain and conflicting factors it is difficult to reduce the cost of the system and improve the reliability of the system simultaneously. In such situations, the decision making is difficult, and the presence of multi-objectives gives rise to multi-objective optimization problem (MOOP), which leads to Pareto optimal solutions instead of a single optimal solution. However in order to make the model more flexible and adaptable to human decision process, the optimization model can be expressed as fuzzy nonlinear programming problems with fuzzy numbers. Thus in a fuzzy environment, a fuzzy multi-objective optimization problem (FMOOP) is formulated from the original crisp optimization problem. In order to solve the resultant problem, a crisp optimization problem is reformulated from FMOOP by taking into account the preference of decision maker regarding cost and reliability goals and then particle swarm optimization is applied to solve the resulting fuzzified MOOP under a number of constraints. The approach has been demonstrated through the case study of a pharmaceutical plant situated in the northern part of India.     

Computerized container-ship load planning: A methodology and evaluation

A heuristic is developed to plan loads for containerized cargo ships. It is designed to serve a port which uses gantry cranes (transtainers) and trucks to handle containers. The model recognizes constraints on ship stability, placing containers in a bay with the proper length, limits on stack height in under-deck bays, limits on stack weight in on-deck bays, refrigerated containers, and the need for support under a container. Provisions are made for the operator to handle overstowage of cargo for different ports and placement of oversize cargo. The model uses minimization of transtainer movement time and minimization of rehandles in the yard as an objective. The heuristic uses strategies for container placement similar to those used in manual load planning. A test of two ships and four voyages at the Port of Portland produced feasible load plans for each voyage. Transtainer movement and rehandling time varied for the four voyages; but on the average, the heuristic reduced a composite material handling measure by 4.8%.     

A genetic algorithm to solve the storage space allocation problem in a container terminal

In this paper, an efficient genetic algorithm (GA) is presented to solve an extended storage space allocation problem (SSAP) in a container terminal. The SSAP is defined as the temporary allocation of the inbound/outbound containers to the storage blocks at each time period with aim of balancing the workload between blocks in order to minimize the storage/retrieval times of containers. An extended version of a SSAP proposed in the literature is considered in this paper in which the type of container affects on making the decision on the allocation of containers to the blocks. In real-world cases, there are different types (as well as different sizes) of containers consisting of several different goods such as regular, empty and refrigerated containers. The extended SSAP is solved by an efficient GA for real-sized instances. Because of existing the several equality constraints in the extended model, the implementation of the GA in order to quick and facilitate achieve to the feasible solutions is one of the outstanding advantages of this paper. The performance of the extended model and proposed GA is verified by a number of numerical examples.     

基于船时效率的岸桥配置优化

在集装箱码头系统中,对船舶进行有效的岸桥配置有助于缓解岸边资源紧张的现状,提高码头的运营效率。针对连续泊位下动态到港船舶的泊位分配和岸桥配置的集成优化问题,对船舶的岸桥配置进行基于船时效率的动态调整,以最小化包括船舶延迟靠泊成本、偏离偏好泊位成本、延迟离港成本和岸桥重新配置成本在内的总成本为目标建立模型,并根据基于船时效率的岸桥配置的调整规则设计了启发式算法,结合遗传算法（GA）对问题进行求解。最终通过算例分析,验证了提出的模型和算法在解决实际港口中泊位分配和岸桥配置问题上的有效性,并通过与未考虑岸桥配置进一步调整的传统GA计算的结果进行比较,证实了提出算法的优化效果。     

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.     

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.