An Analysis of Policy Making for Dry Port Location and Capacity: A Case study on Alexandria

Container terminal capacity is a crucial issue for port and terminal operators nowadays as it is one of the key points for their success and increasing their competitive market position in the maritime industry. Therefore, researchers have tried to find solutions for the over capacity problem that faces many terminal operators. This research suggests dry ports as one of the most suitable solution for this problem through proposing a structured framework to adopt the right policy decisions for Dry Port location and capacity. To achieve the presented framework some areas were addressed in detail to have the full picture clear. The current status of the global container sector was assessed, also, the main capacity problems of container terminals with a view to reviewing the suggested solutions was investigated, hence the need for dry ports. In addition, policies for providing optimal location and capacity decisions for container terminals were identified. A technique that supports assessing container terminal location and capacity policy decisions with particular reference to dry ports were developed. Moreover, a case study on Alexandria International Container Terminal for validating the results was conducted. The current research was facilitated by experts from the maritime transport industry, through the application of the Delphi Technique. Applying such a technique enables collaborating experts to share experience modify statements and re-asking to reach a final exact answer that could be generalized. The consensus achieved will help build knowledge and understanding of potential Dry Ports’ policies of the maritime transport sector. This research seeks to make an original contribution to knowledge by developing a structured framework to identify policy decisions for location and capacity of Dry Ports using a Delphi technique as a support tool for terminal managers and operators, port planners, policy makers, and investors in deciding decisions relevant to Dry Port investment.Arab Academy for science & Technology & Maritime Transpor

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

Evolutionary computing for routing and scheduling applications

Ph.DDOCTOR OF PHILOSOPH

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

Development Of Models And Solution Methods For Different Drayage Applications

In the last decades, intermodal freight transport is becoming more attractive in the global supply chains and freight transport policy makings. Intermodal freight transport provides a cost-effective, reliable, and efficient movement of freight by utilizing the strengths of different transport modes. The initial and final segment of intermodal freight transport, performed by truck, is known as “drayage.” The scheduling of truck movements in drayage operation within the service area of an intermodal terminal is an operational problem which leads to a truck scheduling problem that determines the efficient schedule of trucks while satisfying all transportation demands and constraints. Drayage accounts for a large percentage of the origin-destination expenses in the intermodal transport. Efficient planning of the drayage operations to improve the economic performance of this operation can increase the efficiency and attractiveness of intermodal transport. The primary objective of this research is to apply operation research techniques to optimize truck movements in drayage operation. The first study in this dissertation considers the drayage problem with time constraints at marine container terminals imposed by the truck appointment system and time-windows at customer locations. A mathematical model is proposed that solve the empty container allocation problem, vehicle routing problem, and appointment booking problem in an integrated manner. This model is an extension of a multiple traveling salesman problem with time windows (m-TSPTW) which is known to be NP-hard (i.e., non-deterministic polynomial-time hard). To solve this model, a reactive tabu search (RTS) algorithm is developed and its accuracy and computational efficiency are evaluated against an industry-established solver IBM ILOG CPLEX. In comparison with the CPLEX, RTS was able to find optimal or near-optimal solution in significantly shorter time. This integrated approach also allows for more accurate evaluation of the effects of the truck appointment system on the drayage operation. The second study extends the drayage literature by incorporating these features in drayage problem: (1) treating tractor, container, and chassis as separate resources which are provided in different locations, (2) ensuring that container and chassis are of the same size and type, (3) considering the possibility that drayage companies can sub-contract the work to owner-operators, and (4) a heterogeneous mix of drayage vehicles (from company fleet and owner-operators) with different start and end locations is considered; drayage company’s trucks start at company’s depot and should return to one of the company’s depots whereas owner-operators’ trucks should return to the same location from where they originated. A mixed-integer quadratic programming model is developed that solves scheduling of tractors, full containers, empty containers, and chassis jointly. A RTS algorithm combined with an insertion heuristic is developed to tackle the problem. The experimental results demonstrated the feasibility of the developed model and solution methodology. The results show that the developed integrated model is capable of finding the optimal solutions and is solvable within a reasonable time for operational problems. This new model allowed us to assess the effectiveness of different chassis supply models on drayage operation time, the percentage of empty movements and air emissions. The fourth work builds on our previous work and extends the integrated drayage scheduling model to consider uncertainty in the (un)packing operation. Recognizing the inherent difficulty in obtaining an accurate probability distribution, this paper develops two new stochastic drayage scheduling models without explicit assumption about the probability distributions of the (un)packing times. The first model assumes that only the mean and variance of the (un)packing times are available, and the second model assumes that the mean as well as the upper and lower bounds of the (un)packing times are available. To demonstrate the feasibility of the developed models, they are tested on problem instances with real-life characteristics. Future work would address the real-time scheduling of drayage problem. It would assume trucks’ locations, travel times, and customer requests are updated throughout the day. We would propose a solution approach for solving such a complex model. The solution approach would be based on re-optimization of the drayage problem and consist of two phases: (1) initial optimization at the beginning of the day, and (2) re-optimization during operation. The third study of this dissertation addresses the impact of a new trend in the North American intermodal terminals in using second-tier facilities on drayage operation. These facilities are located outside the terminals and are used to store loaded containers, empty containers, and chassis. This work builds on our previous work and extends the integrated drayage scheduling model to incorporate these features into drayage problem: (1) trucks do not have to wait at customers’ locations during the packing and unpacking operations, (2) drayage operations include a drop yard (i.e., second-tier facility) for picking up or/and dropping off loaded containers outside the marine container terminal, and (3) the job requests by customers is extended to include empty container pickup, loaded container pickup, empty container delivery, and loaded container delivery. As the mathematical model is an extension of the m-TSPTW, a RTS combined with an insertion heuristic developed by the authors is used to solve the problems

An Agent-based Approach for Improving the Performance of Distributed Business Processes in Maritime Port Community

In the recent years, the concept of “port community” has been adopted by the maritime transport industry in order to achieve a higher degree of coordination and cooperation amongst organizations involved in the transfer of goods through the port area. The business processes of the port community supply chain form a complicated process which involves several process steps, multiple actors, and numerous information exchanges. One of the widely used applications of ICT in ports is the Port Community System (PCS) which is implemented in ports in order to reduce paperwork and to facilitate the information flow related to port operations and cargo clearance. However, existing PCSs are limited in functionalities that facilitate the management and coordination of material, financial, and information flows within the port community supply chain. This research programme addresses the use of agent technology to introduce business process management functionalities, which are vital for port communities, aiming to the enhancement of the performance of the port community supply chain. The investigation begins with an examination of the current state in view of the business perspective and the technical perspective. The business perspective focuses on understanding the nature of the port community, its main characteristics, and its problems. Accordingly, a number of requirements are identified as essential amendments to information systems in seaports. On the other hand, the technical perspective focuses on technologies that are convenient for solving problems in business process management within port communities. The research focuses on three technologies; the workflow technology, agent technology, and service orientation. An analysis of information systems across port communities enables an examination of the current PCSs with regard to their coordination and workflow management capabilities. The most important finding of this analysis is that the performance of the business processes, and in particular the performance of the port community supply chain, is not in the scope of the examined PCSs. Accordingly, the Agent-Based Middleware for Port Community Management (ABMPCM) is proposed as an approach for providing essential functionalities that would facilitate collaborative planning and business process management. As a core component of the ABMPCM, the Collaborative Planning Facility (CPF) is described in further details. A CPF prototype has been developed as an agent-based system for the domain of inland transport of containers to demonstrate its practical effectiveness. To evaluate the practical application of the CPF, a simulation environment is introduced in order to facilitate the evaluation process. The research started with the definition of a multi-agent simulation framework for port community supply chain. Then, a prototype has been implemented and employed for the evaluation of the CPF. The results of the simulation experiments demonstrate that our agent-based approach effectively enhances the performance of business process in the port community

Competitiveness and strategic positioning of seaports: the case of Iberian Seaports

The global market, with its extensive business networks and complex logistics systems, poses a high degree of uncertainty to the seaport industry and leaves seaport managers facing questions over just how to effectively respond to the ongoing market dynamics. Over the years, competition among seaports has intensified due to a number of structural changes taking place in seaport systems. Firstly, seaport hinterlands have extended well beyond national boundaries as a result of improvements to logistics and transport infrastructure. Secondly, the seaport industry is becoming increasingly concentrated through mergers and alliances. Thirdly, seaports are no longer mere interface points between land and sea or air. As communication technology advances and trade liberalization facilitates globalization, the role of seaports in the supply chain is changing. Seaports have now become one of the most dynamic links in international transport networks. There is already a clear consensus in the literature around the sheer importance of seaports to national economies, especially to those heavily dependent on international trade. Taking into account the vital importance of seaports directly or indirectly to the economy of any country, and especially to those of Portugal and Spain, this research seeks to analyse the competitiveness and strategic positioning of Iberian seaports. In accordance with the seaport context set out above, the following four research questions are raised: i) are there different prevailing levels of competitiveness at Iberian seaports? ii) what are the key factors to seaport competitiveness from the stakeholder’s perspective? Do perceptions of the importance of these factors differ between users and service providers? iii) how are Iberian seaports strategically positioned within the Iberian range? iv) What is the contribution of logistics resources to the competitiveness and performance of this sector? To approach the level of competitiveness dimension, we measure seaport efficiency through applying an alternative Data Envelopment Analysis (DEA) methodology for cross sectional data from 2009 and the appropriate DEA methods (contemporaneous and windows analysis) for panel data (2005-2009). The results suggest that levels of Iberian seaport efficiency differ significantly not only from seaport to seaport but also at each seaport over the course of time. The study also identifies both the contribution of inputs/outputs to this seaport efficiency and the causes of inefficiency. Through the Analytic Hierarchy Process (AHP), we study the key factors to seaport competitiveness from the perspectives of stakeholders as well as the strength of their respective preferences. The Delphi approach was deployed for the preliminary stages of factor selection. The results reveal how seaports users and seaport service providers disagree over the importance of the key factors to seaport competitiveness. The results empirically demonstrate that vessel turnaround time is the most important factor to seaport competitiveness from perception of its users. However, from that of the seaport authorities and terminal operators, seaport facilities and equipment is the most important factor. The importance-performance matrix analysis also confirms that the vessel turnaround time that proves most important to users is also the factor on which the seaports do not perform well. Therefore, the service providers of Iberian seaports need to focus on improving its performance in this field. To study strategic seaport positioning, we apply the BCG (Boston Consulting Group) matrix as a strategic tool generating an evolutionary perspective. The findings reveal a better positioning of Spanish seaports in relation to total traffic. According to the time series analyzed (1992-2009), the strategic positioning of most seaports in the BCG matrix had changed from the first to the third period. Furthermore, in terms of container traffic, the results identify the seaports of Algeciras, Valencia, and Barcelona as having attained a remarkable position of leadership. With the purpose of analyzing the contribution of resource logistics to seaport performance, the linear additive Multi Criterion Analysis (MCA) and the Principal Components Analysis (PCA) model were adopted. The model incorporates the contribution of two different performance indicators, operational performance and physical capacity, measured by several indicators. The physical capacity indicators considered are logistics resources. Study results show operational performance contributed 48.77% whilst physical capacity represented 51.23% of overall performance with the majority of seaports revealing a direct proportionality between their positioning in terms of physical capacity and their overall performance positioning.This work was financially supported by the Fundação para a Ciência e Tecnologia (FCT) subsidized by the Fundo Social Europeu (FSE) and funds from the MCTES State Budget under the QREN - POPH - Type 4.1 - Advanced Training