Optimization of empty container movements using street-turn: Application to Valencia hinterland

Empty maritime container logistics is one of the most relevant costs for shipping companies. In this paper two mathematical models (based on two different container movement patterns, i.e. with and without street-turns) were defined to optimize land empty container movements among shippers, consignees, terminals and depots, along with minimizing storage costs. One of the proposed optimization models was embedded in a simple Decision Support System (DSS) and then tested with real data, based on the operations in Valencia s (Spain) hinterland. The results obtained confirm the benefits of implementing these kinds of models for the company, and additional experiments assess and quantify the advantage of using the more complex approach that is able to implement street-turn patterns.This research has been funded by the Spanish Ministry of Science and Innovation through Grant DPI2010-16201 and FEDER.Furió, S.; Andrés Romano, C.; Adenso Díaz, B.; Lozano Segura, S. (2013). Optimization of empty container movements using street-turn: Application to Valencia hinterland. Computers and Industrial Engineering. 66(4):909-917. https://doi.org/10.1016/j.cie.2013.09.003S90991766

Maritime Empty Container Repositioning with Inventory-based Control

Ph.DDOCTOR OF PHILOSOPH

Global and International Logistics

This book contains 10 reviewed papers published as a Special Issue “Global and International Logistics” in the journal Sustainability, edited by Prof. Dr. Ryuichi Shibasaki, Prof. Dr. Daisuke Watanabe, and Dr. Tomoya Kawasaki. The topics of the papers contain the impact of logistics development under the China’s Belt and Road initiative (BRI) by using the improved gravity model, strategies against barriers to the BRI from a logistics and supply chain management perspective, the dynamic interaction between international logistics, and cross-border e-commerce trade, the effect of China’s restrictive programs on the international trade of waste products, the empty container repositioning problem of shipping companies with foldable containers, port capacity and connectivity improvement in the hub and feeder network in Indonesia, GHG emission scenarios for the maritime shipping sector using system dynamics, incorporating a shipping and shipbuilding market model, the emission inventory and bunker consumption from a LNG fleet from an automatic identification system database, the factors that can help select between land transport and maritime shipping in long-distance inter-regional cross-border transport, and container transport simulations in Myanmar with the global logistics intermodal network assignment model including both maritime shipping and land transport in the land-based Southeast Asia region. Some papers are related to the 8th International Conference on Transportation and Logistics (T-LOG 2020) which was held online on 6–7 September 2020 hosted by Universitas Internasional Semen Indonesia

Robust optimisation of dry port network design in the container shipping industry under uncertainty

PhD ThesisThe concept of dry port has attracted the attention of many researchers in the field of containerised transport industry over the past few decades. Previous research on dry port container network design has dealt with decision-making at different levels in an isolated manner. The purpose of this research is to develop a decision-making tool based on mathematical programming models to integrate strategic level decisions with operational level decisions. In this context, the strategic level decision making comprises the number and location of dry ports, the allocation of customers demand, and the provision of arcs between dry ports and customers within the network. On the other hand, the operational level decision making consists of containers flow, the selection of transportation modes, empty container repositioning, and empty containers inventory control. The containers flow decision involves the forward and backward flow of both laden and empty containers. Several mathematical models are developed for the optimal design of dry port networks while integrating all these decisions. One of the key aspects that has been incorporated in this study is the inherent uncertainty of container demands from end customers. Besides, a dynamic setting has to be adopted to consider the inevitable periodic fluctuation of demands. In order to incorporate the abovementioned decision-making integration with uncertain demands, several models are developed based on twostage stochastic programming approach. In the developed models, the strategic decisions are made in the first stage while the second-stage deals with operational decisions. The models are then solved through a robust sample average approximation approach, which is improved with the Benders Decomposition method. Moreover, several acceleration algorithms including multi-cut framework, knapsack inequalities, and Pareto-optimal cut scheme are applied to enhance the solution computational time. The proposed models are applied to a hypothetical case of dry port container network design in North Carolina, USA. Extensive numerical experiments are conducted to validate the dry port network design models. A large number of problem instances are employed in the numerical experiments to certify the capability of models. The quality of generated solutions is examined via a statistical validation procedure. The results reveal that the proposed approach can produce a reliable dry port container network under uncertain environment. Moreover, the experimental results underline the sensitivity of the configuration of the network to the inventory holding costs iii and the value of coefficients relating to model robustness and solution robustness. In addition, a number of managerial insights are provided that may be widely used in container shipping industry: that the optimal number of dry ports is inversely proportional to the empty container holding costs; that multiple sourcing is preferable when there are high levels of uncertainty; that rail tends to be better for transporting laden containers directly from seaports to customers with road being used for empty container repositioning; service level and fill rate improve when the design targets more robust solutions; and inventory turnover increases with high levels of holding cost; and inventory turnover decreases with increasing robustness

Ocean container transport in global supply chains: Overview and research opportunities

This paper surveys the extant research in the field of ocean container transport. A wide range of issues is discussed including strategic planning, tactical planning and operations management issues, which are categorized into six research areas. The relationships be- tween these research areas are discussed and the relevant literature is reviewed. Representative models are selected or modified to provide a flavour of their functions and application context, and used to explain current shipping practices. Future research opportunities bearing in mind the emerging phenomena in the field are discussed. The main purpose is to raise awareness and encourage more research into and application of operations management techniques and tools in container transport chains

A Literature Review, Container Shipping Supply Chain: Planning Problems and Research Opportunities

This paper provides an overview of the container shipping supply chain (CSSC) by taking a logistics perspective, covering all major value-adding segments in CSSC including freight logistics, container logistics, vessel logistics, port/terminal logistics, and inland transport logistics. The main planning problems and research opportunities in each logistics segment are reviewed and discussed to promote further research. Moreover, the two most important challenges in CSSC, digitalization and decarbonization, are explained and discussed in detail. We raise awareness of the extreme fragmentation of CSSC that causes inefficient operations. A pathway to digitalize container shipping is proposed that requires the applications of digital technologies in various business processes across five logistics segments, and change in behaviors and relationships of stakeholders in the supply chain. We recognize that shipping decarbonization is likely to take diverse pathways with different fuel/energy systems for ships and ports. This gives rise to more research and application opportunities in the highly uncertain and complex CSSC environment.</jats:p

Analysis of Empty Container Accumulation Problem of Container Ports

In this study, the empty container problem is evaluated by quantification of factors related to empty container accumulation as well as alternative ways that can be followed for solutions. The study is mainly constructed as two parts; the first part is on identifying involving factors by using DEMATEL and the second part deals with alternative solutions by applying TOPSIS method. The main causes affecting empty containers were found as trading imbalance, irregular distribution, delivery time, unbalanced freight charges and inadequate port management. Finally, based on applied Multi Criteria Decision Making approach, this study suggests that empty container problem can be solved by sharing infrastructures and equipment among logistic companies, allocating storage areas for empty containers outside the ports and following robust fast custom regulations

Models and algorithms for the empty container repositioning and its integration with routing problems

The introduction of containers has fostered intermodal freight transportation. A definition of intermodality was provided by the European Commission as “a characteristic of a transport system whereby at least two different modes are used in an integrated manner in order to complete a door-to-door transport sequence”. The intermodal container transportation leads to several benefits, such as higher productivity during handling phases and advantages in terms of security, losses and damages. However, the distribution of containers comes with a drawback: due to directional imbalances in freight flows, some areas tend to accumulate unnecessary empty containers, while others face container shortages. Several planning models were developed for carriers in order to manage both loaded and empty containers profitably. However, they were built to operate under normal circumstances, neglecting the fact that networks are increasingly affected by both uncertainty and vulnerability, which may result in disruptions. The thesis aims to survey whether the impact of uncertainty can be mitigated by a stochastic programming approach, in which disruptions and normal operations are both foreseen as possible futures or scenarios. This approach is carried out by a multi-scenario optimization model in which scenarios are linked by non-anticipativity conditions. The empty container repositioning becomes even more challenging and difficult when integrated with routing problems. In fact, carriers often face problems in which they must determine simultaneously how many empty containers are carried by a fleet of vehicles and which routes must be followed by these vehicles. These problems typically arise in inland networks, in which one must plan the distribution by trucks of loaded and empty containers to customers. The thesis addresses this type of vehicle routing problems, which are motivated by a real case study occurred during the collaboration with a carrier that operates in the Mediterranean Sea in door-to-door modality. The carrier manages a fleet of trucks based at the port. Trucks and containers are used to service two types of transportation requests, the delivery of container loads from the port to import customers, and the shipment of container loads from export customers to the port. The thesis addresses two problems which differ in the composition of the fleet of trucks. The first problem involves a heterogeneous fleet of trucks that can carry one or two containers. We present a Vehicle Routing Problem with backhauls, load splits into multiple visits, and the impossibility to separate trucks and containers during customer service. Then, we formalize the problem by an Integer Linear Programming formulation and propose an efficient meta-heuristic algorithm able to solve it. The meta-heuristic determines the initial solution by a variant of the Clarkeand-Wright algorithm, and improves it by several local search phases, in which both node movements and truck swaps are implemented. The second problem involves a homogeneous fleet of trucks that can carry more than a container. As a consequence, the identification of routes can be more difficult. We present and formalize the associated Vehicle Routing Problem by an Integer Linear Programming formulation. Then we propose an efficient adaptive guidance meta-heuristic algorithm able to solve it. The meta-heuristic determines an initial feasible solution by a Tabu Search step, and next improves this solution by appropriate adaptive guidance mechanisms

Models and algorithms for the empty container repositioning and its integration with routing problems

The introduction of containers has fostered intermodal freight transportation. A definition of intermodality was provided by the European Commission as “a characteristic of a transport system whereby at least two different modes are used in an integrated manner in order to complete a door-to-door transport sequence”. The intermodal container transportation leads to several benefits, such as higher productivity during handling phases and advantages in terms of security, losses and damages. However, the distribution of containers comes with a drawback: due to directional imbalances in freight flows, some areas tend to accumulate unnecessary empty containers, while others face container shortages. Several planning models were developed for carriers in order to manage both loaded and empty containers profitably. However, they were built to operate under normal circumstances, neglecting the fact that networks are increasingly affected by both uncertainty and vulnerability, which may result in disruptions. The thesis aims to survey whether the impact of uncertainty can be mitigated by a stochastic programming approach, in which disruptions and normal operations are both foreseen as possible futures or scenarios. This approach is carried out by a multi-scenario optimization model in which scenarios are linked by non-anticipativity conditions. The empty container repositioning becomes even more challenging and difficult when integrated with routing problems. In fact, carriers often face problems in which they must determine simultaneously how many empty containers are carried by a fleet of vehicles and which routes must be followed by these vehicles. These problems typically arise in inland networks, in which one must plan the distribution by trucks of loaded and empty containers to customers. The thesis addresses this type of vehicle routing problems, which are motivated by a real case study occurred during the collaboration with a carrier that operates in the Mediterranean Sea in door-to-door modality. The carrier manages a fleet of trucks based at the port. Trucks and containers are used to service two types of transportation requests, the delivery of container loads from the port to import customers, and the shipment of container loads from export customers to the port. The thesis addresses two problems which differ in the composition of the fleet of trucks. The first problem involves a heterogeneous fleet of trucks that can carry one or two containers. We present a Vehicle Routing Problem with backhauls, load splits into multiple visits, and the impossibility to separate trucks and containers during customer service. Then, we formalize the problem by an Integer Linear Programming formulation and propose an efficient meta-heuristic algorithm able to solve it. The meta-heuristic determines the initial solution by a variant of the Clarkeand-Wright algorithm, and improves it by several local search phases, in which both node movements and truck swaps are implemented. The second problem involves a homogeneous fleet of trucks that can carry more than a container. As a consequence, the identification of routes can be more difficult. We present and formalize the associated Vehicle Routing Problem by an Integer Linear Programming formulation. Then we propose an efficient adaptive guidance meta-heuristic algorithm able to solve it. The meta-heuristic determines an initial feasible solution by a Tabu Search step, and next improves this solution by appropriate adaptive guidance mechanisms

Sea Container Terminals

Due to a rapid growth in world trade and a huge increase in containerized goods, sea container terminals play a vital role in globe-spanning supply chains. Container terminals should be able to handle large ships, with large call sizes within the shortest time possible, and at competitive rates. In response, terminal operators, shipping liners, and port authorities are investing in new technologies to improve container handling infrastructure and operational efficiency. Container terminals face challenging research problems which have received much attention from the academic community. The focus of this paper is to highlight the recent developments in the container terminals, which can be categorized into three areas: (1) innovative container terminal technologies, (2) new OR directions and models for existing research areas, and (3) emerging areas in container terminal research. By choosing this focus, we complement existing reviews on container terminal operations