Transshipment Network Research Articles

Modeling Dynamic Bargaining and Stability in a Star-Shaped Trans-Shipment Network

The star-shaped trans-shipment network causes the retailer’s bargaining power to be different, which leads to the misalignment of trans-shipment profit. Aimed at this, we take retailers and the trans-shipment paths as the nodes and edges of the trans-shipment network. Based on this, we model the multilateral negotiations between the central retailer and the local retailer and adopt the Generalized Nash Bargaining game to derive the optimal solution of the value function for the incomplete trans-shipment network under the bargaining mechanism. Furthermore, we reveal the convexity of the optimal trans-shipment value function and give the condition that the allocation of the bargaining mechanism is in the core. Based on this, we introduce the concept of pairwise Nash equilibrium and show the star-shaped trans-shipment network is the optimal endogenous formation of the trans-shipment network. In practice, the central retailer should introduce as many local retailers as possible to join this trans-shipment alliance, which will achieve Pareto improvement. Meanwhile, the central retailer should order as many as possible. Finally, it is more appropriate to establish a star-shaped trans-shipment network when one retailer has stronger negotiation power compared to other retailers in a distribution system, which not only ensures the stability of the allocation of trans-shipment profits but also the stability of the trans-shipment network.

Container port influence: a spatial diffusion analysis of global transshipments

ABSTRACTThis paper examines the global diffusion patterns of over 1000 ports’ container traffic from 2013 to 2022 to understand port influence dominance. Based on an influence maximization model of direct and indirect diffusion paths, it shows that two ports, Rotterdam and Singapore, consistently exert a disproportionate influence on other ports capturing the Matthew effect which proposes that influence begets influence. Initial advantage in capturing the global transshipment networks enabled both ports to widen and strengthen their influence with time. Despite their lead, Busan’s rise indicates it is possible to catch up. However, the paper also found a reversed Matthew effect for Hamburg and Zhoushan indicating that initial advantage can vaporize if not sustained. The findings imply that ports’ early capacity to capture the global transshipment market can lead to sustained advantage but such advantage can also be developed over time if port managers pay attention to indirect paths of capturing the global container market.

Analyzing the Vulnerabilities in a Transshipment Network: A Bilevel Programming Approach

As one of the most common types of networks, transshipment networks face certain risks in their daily operations. This risk either stems from a deliberate intervention in the process or from an unpredictable natural effect. The owner of the network normally aims to minimize the total cost of the transportation, while a rival or an opponent might attempt to intervene in the process and cause an increase in the costs. Unpredictable natural setbacks, on the other hand, can also have a negative impact on the network necessitating decision-makers to be more vigilant, especially for the worst-case consequences of network disruptions. The problem can be designed as a bilevel mathematical model. In this study, we develop a bilevel max-min model considering that the arcs in a transshipment network are liable to a disruption imposed by an intervenor. We present an original model with a novel solution approach to identify vulnerabilities in the arcs of a given transshipment network. The results reveal the most vulnerable arcs in the network, which have the highest negative impact on transportation costs when a disruption occurs. The decision-makers can use such results to analyze the risk in distribution networks such as electrical grids and develop associated measures to decrease the cost and increase the flexibility of the distribution systems. The model also enables decision makers with a methodical understanding of worst cases if the distribution network is interrupted for some reason.

Transshipment network design for express air cargo operations in China

We introduce a novel multimodal (ground and air transportation) network design model with transshipments for the transport of express cargo with heterogeneous service classes (i.e., next morning delivery, and next day delivery). We formulate this problem using a novel path-based mixed-integer program which seeks to maximize the demand (weight) served. We investigate the value of the proposed transshipment network under various operational conditions and by benchmarking against a direct shipment network and a network with a single transshipment point which mimics a classical star-shaped hub-and-spoke network. Our extensive computational study with real-world data from ShunFeng (SF) Express reveals that the integration of ground and air transportation improves the coverage and that transshipment enables serving a large number of origin–destination pairs with a small number of cargo planes. Importantly, we show that by simplifying handling, i.e., employing cross-docking rather than time-consuming sortation, a transshipment network can transport express cargo fast enough to meet demanding delivery deadlines. Finally, we find that increasing the efficiency of intra-city operations and extending the nightly operating time window are the most effective operational adjustments for further improving the performance of the proposed transshipment network.

Identifying Central Carriers and Detecting Key Communities Within the Global Fish Transshipment Networks

To effectively monitor fisheries resources and combat illegal, unreported, and unregulated fishing, human labor exploitation onboard fishing vessels amongst other crimes, such as the trafficking of weapons, humans, and narcotics, it is important that more attention is paid to the likely facilitators of these activities, one of these being at-sea transshipment of fish. Even though transshipment is a common practice that has taken place for decades, little is known about the overall networks, operational practices, and global spatial patterns of thecentral actorsinvolved in such activities. This research aims to fill that knowledge gap by understanding the networks of activities of the actors who play a central role in these global transshipment activities. Using data from Global Fishing Watch on global transshipment events that took place between 2015 and 2020, this research (a) identifies thecentral carriersinvolved in transshipment events, (b) visualizes their networks of activities and interactions with fishing vessels, (c) examines the spatial distribution of their activities; and (d) determines whether these vessels use open-registry flags when engaging in transshipments, and if so, which. In exploring the role that central actors play within networks of transshipments, targeted mechanisms can be designed to better monitor such activities.

Transshipment Network Design for Express Air Cargo Operations in China

Transshipment Network Design for Express Air Cargo Operations in China

Bike-Repositioning Using Volunteers: Crowd Sourcing with Choice Restriction

Motivated by the Bike Angels Program in New York's Citi Bike and Boston's Blue Bikes, we study the use of (registered) volunteers to re-position empty bikes for riders in a bike sharing system. We propose a method that can be used to deploy the volunteers in the system, based on the real time distribution of the bikes in different stations. To account for (random) route demand in the network, we solve a related transshipment network design model and construct a sparse structure to restrict the re-balancing activities of the volunteers (concentrating re-balancing activities on essential routes). We also develop a comprehensive simulation model using a threshold-based policy to deploy the volunteers in real time, to test the effect of choice restriction on volunteers (suitably deployed) to re-position bikes. We use the Hubway system in Boston (with 60 stations) to demonstrate that using a sparse structure to concentrate the re-balancing activities of the volunteers, instead of allowing all admissible flows in the system (as in current practice), can reduce the number of re-balancing moves by a huge amount, losing only a small proportion of demand satisfied.

An extreme‐point tabu‐search algorithm for fixed‐charge network problems

AbstractWe propose a new algorithm for fixed‐charge network flow problems based on ghost image (GI) processes as proposed in Glover (1994) and adapted to fixed‐charge transportation problems in Glover et al. (2005). Our GI algorithm iteratively modifies an idealized representation of the problem embodied in a parametric GI, enabling all steps to be performed with a primal network flow algorithm operating on the parametric GI. Computational testing is carried out on well‐known problems from the literature plus a new set of large‐scale fixed‐charge transportation and transshipment network instances. We also provide comparisons against CPLEX 12.8 and demonstrate that the new GI algorithm with tabu search (TS) is effective on large problem instances, finding solutions with statistically equivalent objective values at least 700 times faster. The attractive outcomes produced by the current GI/TS implementation provide a significant advance in our ability to solve fixed‐cost network problems efficiently and invites its use for larger instances from a variety of application domains.

An auction-enabled collaborative routing mechanism for omnichannel on-demand logistics through transshipment

Nowadays’ on-demand logistics operations are carried out on separate delivery networks from competitive contractors, with redundant resources and high costs. This article proposes a new paradigm to deal with industrial and societal challenges, developing an auction-enabled collaborative routing mechanism for omnichannel on-demand logistics in a real-time transshipment network. We consider an online service platform for real-time management of on-demand pickup and delivery tasks, where multiple freight shippers can trade with multiple freight carriers. Freight shippers are retailers or individual customers, while freight carriers are a group of logistics service providers. The platform acts as the auctioneer. A two-stage combinational auction mechanism is designed for dynamic on-demand task (re)allocation. Tactical-level auctioning and operational-level routing decisions are optimized together. The transshipment-based task generation method is used to identify uneconomic paths from carrier’s real-time network for outsourcing. A transshipment-based routing algorithm is developed to enable each carrier to make decentralized decisions for network reconstruction and transportation bidding. Our model aims to improve the overall social welfare while bringing benefits to stakeholders involved. The computational results have shown positive society impacts. Specifically, shippers’ payments can be saved while carriers’ profits are increased compared with other operative models which have been investigated in previous research studies or industry. In addition, a substantial reduction in CO2 emissions and vehicles required can be achieved. The main reason for the improvement in social welfare is due to the optimal network achieved through collaboration. We also numerically analyze the impacts of three key factors: growth in demand density, urgency of tasks and flexible auction interval.

A transshipment model for logistics management at Indian Oil Corporation

Three refineries of the Indian Oil Corporation procure crude oil from suppliers, at production sites in the Persian Gulf, West Africa, North Africa, West Asia, and India. The crude oil is shipped to two ports in the state of Gujarat, India, by large tankers and medium sized vessels. From these two ports, the crude oil is pumped to the refineriesviapipelines. The refineries have known capacity, that are different for the two types of crude oil. In this paper, the scaled-up problem has been modelled, as a transshipment network. Next, the concrete instance of the problem, has been solved using an LP solver. This was followed by post-optimality analysis of the solution. The flow values on all arcs, and optimal product mix, validate actual decisions. Precise shipping requirements obtained from the solution, are shared in advance with marine transporters to improve supply chain coordination.

Distribution planning with random demand and recourse in a transshipment network

Abstract In this paper we consider a distribution planning problem in a transshipment network under stochastic customer demand, to account for uncertainty faced in real-life applications when planning distribution activities. To date, considerations of randomness in distribution planning networks with intermediate facilities have received very little attention in the literature. We address this gap by modeling uncertainty in a distribution network with an intermediate facility, and providing insight on the benefit of accounting for randomness at the distribution planning phase. The problem is studied from the perspective of a third-party logistics provider (3PL) that is outsourced to handle the logistics needs of its customers; the 3PL uses a consolidation center to achieve transportation cost savings. We formulate a two-stage stochastic programming model with recourse that aims to minimize the sum of transportation cost, expected inventory holding cost and expected outsourcing cost. The recourse variables ensure that the problem is feasible regardless of the realization of demand, by allowing the option of using a spot market carrier if demand exceeds capacity. We propose a flow-based formulation with a nonlinear holding cost component in the objective function. We then develop an alternative linear path-based formulation that models the movement of freight in the network as path variables. We apply Sample Average Approximation (SAA) to solve the problem, and show that it results in reasonable optimality gaps for problem instances of different sizes. We conduct extensive testing to evaluate the benefits of our proposed stochastic model compared to its deterministic counterpart. Our computational experiments provide managerial insight into the robustness and cost-efficiency of the distribution plans of our proposed stochastic model, and the conditions under which our model achieves significant distribution cost savings.

Locating switches

In this paper, a novel problem in transshipment networks has been proposed. The main aims of this paper are to introduce the problem and to give useful tools for solving it both in exact and approximate ways. In a transshipment network it is important to decide which are the best paths between each pair of nodes. Representing the network by a graph, the union of thesepaths is a delivery subgraph of the original graph which has all the nodes and some edges. Nodes in this subgraph which are adjacent to more than two nodes are called switches because when sending the flow between any pair of nodes, switches on the path must adequately direct it. Switches are facilities which direct flows among users. The installation of a switch involves the installation of adequate equipment and thus an allocation cost. Furthermore, traversing a switch also implies a service cost or allocation cost. The Switch Location Problem is defined as the problem of determining which is the delivery subgraph with the total lowest cost. Two of the three solutions approaches that we propose are decomposition algorithms based on articulation vertices, the exact and the math-heuristic ones. These two approaches could be embedded in expert systems for locating switches in transshipment networks. The results should help a decision maker to select the adequate approach depending on the shape and size of the network and also on the external time-limit. Our results show that the exact approach is a valuable tool if the network has less than 1000 nodes. Two upsides of our heuristics are that they do not require special networks and give good solutions, gap-wise. The impact of this paper is twofold: it highlights the difficulty of adequately locating switches and it emphasizes the benefit of decomposing algorithms.

Mixed Integer Linear Programming Optimization of Multi-Node Transportation Transshipment Network

Transportation network is time bound supply mechanism and it involves multiple levels. It is beneficial for an organization to identify optimal transportation routes by exploring different options. This practice can help in minimizing the transportation costs and Optimizing the delivery time. In this study, multiple levels of transportation transshipment network are considered and by adopting Mixed Integer Linear Programming (MILP), cost of transportation network is minimized. A comparison with the existing cost indices is provided for effectiveness of the tool used. Result indicates an improvement in the cost saving and comparison with the initial results suggests cost saving by 9.41% in transporting raw materials from depot to the factory level while 8.7% cost saving is achieved in transshipment of finished goods from warehouses to distribution centers. Overall, the total cost is reduced by 18.17% which is a significant improvement and can be translated into profit margin of the production supply chain. We also generalize the findings of the study by assessing the statistical robustness of the results.

Mixed Integer Linear Programming Optimization of Multi-Node Transportation Transshipment Network

Transportation network is time bound supply mechanism and it involves multiple levels. It is beneficial for an organization to identify optimal transportation routes by exploring different options. This practice can help in minimizing the transportation costs and Optimizing the delivery time. In this study, multiple levels of transportation transshipment network are considered and by adopting Mixed Integer Linear Programming (MILP), cost of transportation network is minimized. A comparison with the existing cost indices is provided for effectiveness of the tool used. Result indicates an improvement in the cost saving and comparison with the initial results suggests cost saving by 9.41% in transporting raw materials from depot to the factory level while 8.7% cost saving is achieved in transshipment of finished goods from warehouses to distribution centers. Overall, the total cost is reduced by 18.17% which is a significant improvement and can be translated into profit margin of the production supply chain. We also generalize the findings of the study by assessing the statistical robustness of the results.

Parametric optimization of long-term multi-area heat and power production with power storage

This paper develops a model and optimization method for multi-area heat and power production with power transmission and storage. The objective function of the model is to minimize the operating costs of the system. The model can be used both for planning optimal system operation, and for simulating the effects of extended production, transmission and storage capacity. The proposed parametric decomposition method is fast enough to solve problems with a large number of hourly models. The parametric decomposition method works in two phases. First, the problem is decomposed into hourly local energy production models without storages and transmission. Parametric linear programming analysis is applied to these models for determining the optimal marginal operating costs as a function of power production. In the second phase, the optimal marginal cost functions are encoded as a linear transshipment network model including storages and transmission network. The network model is solved using generic sparse linear programming software. The operation of each production plant is determined based on the network solution. The decomposition method was validated by comparing it against an integrated linear programming model. The decomposition method demonstrates good accuracy and solves yearly models up to 30 times faster than the integrated model.

Co-opetition in enhancing global port network resiliency: A multi-leader, common-follower game theoretic approach

Ports are key elements of global supply chains, providing connection between land- and maritime-based transportation modes. They operate in cooperative, but competitive, co-opetitive, environments wherein individual port throughput is linked through an underlying transshipment network. Short-term port performance and long-term market share can be significantly impacted by a disaster event; thus, ports plan to invest in capacity expansion and protective measures to increase their reliability or resiliency in times of disruption. To account for the co-opetition among ports, a bi-level multiplayer game theoretic approach is used, wherein each individual port takes protective investment decisions while anticipating the response of the common market-clearing shipping assignment problem in the impacted network. This lower-level assignment is modeled as a cost minimization problem, which allows for consideration of gains and losses from other ports decisions through changes in port and service capacities and port cargo handling times. Linear properties of the lower-level formulation permit reformulation of the individual port bi-level optimization problems as single-level problems by replacing the common lower-level by its equivalent Karush Kuhn Tucker (KKT) conditions. Simultaneous consideration of individual port optimization problems creates a multi-leader, common-follower problem, i.e. an unrestricted game, that is modeled as an Equilibrium Problem with Equilibrium Constraints (EPEC). Equilibria solutions are sought by use of a diagonalization technique. Solutions of unrestricted, semi-restricted and restricted games are analyzed and compared for a hypothetical application from the literature involving ports in East Asia and Europe. The proposed co-opetitive approach was found to lead to increased served total demand, significantly increased market share for many ports and improved services for shippers.

Analysis of the development potential of bulk shipping network on the Yangtze River

ABSTRACTIn the past decades, a multilayer transshipment network of bulk shipping has been formed along the Yangtze River so as to support the fast development of Chinese iron and steel industry. Yet with the decrease of iron ore trade in China since 2014, the bulk port system on Yangtze River probably will be subject to change in the future. Under this background, this paper aims to analyze the development potential of Yangtze River bulk ports system with a focus on iron ore transshipment. To realize this objective, we firstly sort out the main transshipment patterns of bulk shipping, and optimize the bulk-shipping network with an optimization model. Several scenarios are then proposed and examined in the model by changing corresponding parameters. Cooperation among ports as one scenario is analyzed by applying core theory in cooperative game. Based on the changes of transshipment plans observed under the various scenarios, we finally ascertain the different development potentials of the system, and provide suggestions to the port operators and local maritime authorities.

The political economy of heroin and crack cocaine in Tanzania

The year 2015 marked a sea change in drug trafficking and drug use in Tanzania. Over three decades, Tanzania had become part of an international trans-shipment network for heroin, and the regular m...

Sales Strategy in Transshipment Networks

This paper discusses the decision to transship inventory in terms of salesman ability or experience. To the best of the authors knowledge, it is the first to characterize trade between retailers at this level of microeconomic detail. The primary transshipment market of interest is the automobile dealer trade network. This paper considers a simplified version of the model in Pairolero (2016). The two retailer version of this model removes the need to consider dense networks, and this paper provides a simpler yet sharper characterization of price relationships between trade and autarky. The primary result is that inexperienced salesmen should never offer the trade because of inability to extract enough buyer value. As the salesman gains experience through selling the models in stock, negotiating ability is likely to increase and thus the ability to extract buyer value in trade increases. Since higher negotiating ability in trade increases trade profitability, trade is more likely to be optimal for experienced salesmen. The results of this paper could be used to advise sale managers on the training of new salesmen.

Endogenous Prices in Dense Transshipment Networks

This paper analyzes optimal dealer pricing in dense dealer trade networks. A homogeneous linking network is developed where each link represents a trade relationship. The trade relationships are governed by an incentive compatibility constraint. The dealer obtaining the model through trade cannot charge the buyer so much that he is better off traveling for the model rather than obtaining it locally through trade. Informally, dense networks are defined to be networks with many nodes. A key insight of the paper is that prices become much easier to analyze as the network becomes dense. Further, the optimal price to charge the distant traveling buyer converges to a fixed value, regardless of network structure. This paper contributes to the transshipment literature in a multitude of ways. First, the paper analyzes optimal pricing as the number of trade relationships changes. Other papers in the literature compare networks with either no trade or complete trade. Second, the incentive compatibility constraint is a novel contribution. Third, the dealer sets three prices simultaneously; the price for the model in stock, the price for a model obtained through trade, and the price to lure the distant buyer. Other papers have not allowed the buyer to advertise different prices in different locations. Finally, existence of pairwise stable equilibrium is proved for dense networks. This and the results on optimal pricing could be used to further determine the optimal number of trade relationships, and thus could provide a better understanding of dealer trade policy than currently exists in the literature.