A collaborative decision support framework for sustainable cargo composition in container shipping services

This paper proposes a decision support system (DSS) for optimizing cargo composition, and resulting stowage plan, in a containership of a shipping company in collaboration with en-route ports in the service. Due to considerable growth in transportation over years, an increasing number of containers are being handled by containerships, and ports consequently. Trade imbalances between regions and recent disruptions, such as LA/LB/Shanghai port congestion, blocking of Suez canal, drought in Panama canal, typhoons at ports, COVID-19 restrictions and the lack- and then over-supply of empty containers, have resulted in an accumulation of containers in exporting ports around the world. These factors have underscored the urgency of sustainability and circular economy within the shipping industry. The demand for container transportation is higher than the ship capacities in the recent times. In this regard, it is essential for shipping companies to generate a cargo composition plan for each service by selecting and transporting containers with relatively high financial returns, while offering a realistic stowage plan considering ship stability, capacity limitations and port operations. Ultimately, the selected containers should enable a ship stowage plan which keeps the ship seaworthy obeying complex stability considerations and minimizes the vessel stay at the ports, and port carbon emissions consequently, through efficient collaboration with en-route ports. This study provides a bi-level programming based DSS that selects the set of containers to be loaded at each port of service and generates a detailed stowage plan considering revenue, stowage efficiency and quay crane operational considerations. Numerical experiments indicate that the proposed DSS is capable of returning high-quality solutions within reasonable solution times for all ship sizes, cargo contents and shipping routes, supporting the principles of the circular economy in the maritime domain.</jats:p

Efficient yard storage in transshipment container hub ports

Ph.DDOCTOR OF PHILOSOPH

Hierarchical modeling and analysis of container terminal operations

After the breakdown of trade barriers among countries, the volume of international trade has grown significantly in the last decade. This explosive growth in international trade has increased the importance of marine transportation which constitutes the major part of the global logistics network. The utilization of containers and container ships in marine transportation has also increased after the eighties due to various advantages such as packaging, flexibility, and reliability. Parallel to the container throughput, the capacities of ships and sizes of fleets as well as the number of terminals have been increased considerably. Substantial pressure of competition on ship operators and terminal managers has forced them to consider the issues regarding operational efficiency more deeply. Thus, the operational efficiency at port container terminals has become the major concern of terminal managers to satisfy the rapid transshipment of goods. In this thesis, we focus on a set of decision problems regarding container terminal operations. Since these problems are interrelated hierarchically, we attempt to model and analyze them consecutively. First, we consider the storage space allocation problem over a rolling horizon as an aggregate planning model. Since the model has the minimum cost flow network structure there exist polynomial time solution procedures via linear programming models. Although ship turnaround time is the principal performance criteria for whole container terminal operations, the total distances traveled by containers in the terminal throughout the planning horizon is determined as the surrogate objective function for the allocation model. The output of the storage space allocation problem is used as the input for the next step of our methodology, namely the location matching model. With the location matching model, the routes of vehicles for each time period have been identified while minimizing the total distance traveled by the vehicles, which reveals the ship turnaround times. The routes that are found subject to the output of storage space allocation models are better than those of random allocation in terms of total distances traveled. Next, the vehicle scheduling problem is discussed for different levels of complexity. The solution procedures proposed for similar problems in the machine scheduling literature are provided. Finally, we discuss the problem of simultaneous vehicle dispatching with precedence constraints. We have modeled the problem as a nonlinear mixed integer programming model and proposed an iterative solution procedure to obtain reasonable solutions in considerable times. Moreover, we have presented the worst-case performance analysis for this heuristic

Key performance indicators for container ports: a case of weighted efficiency gains from operations (WEGO) in South Africa.

Masters Degree. University of KwaZulu-Natal, Durban.South Africa is a developing country, within which the volume of exports and imports plays a significant role in the local economy, and therefore ports are critical gateways to support international trade, which ensures uninterrupted movement of goods in the global supply chain. Transnet National Ports Authority (TNPA) in South Africa acts as the ports’ landlord. The institution is responsible for the funding and administration of local ports. Various authorities including businesses raise concerns about inefficiencies in South African ports. The dominant factors are poor performance and high tariffs. These factors have been explored by previous studies and benchmark studies that were conducted by Ports Regulator of South Africa (PRSA). Durban container port is characterised with poor performance particular for container handling and high tariffs for specific port users. The Ports Regulator of South Africa responded to this concern of high tariffs and poor performance by establishing a new element into tariff Methodology called Weighted Efficiency Gains from Operations (WEGO). This is a tool aimed to improve port operational performance, applying to all South African ports. This study aims to assess and explore Key Performance Indicators (KPIs) selected to determine WEGO. TNPA intends to link performance gains for operations to the tariff methodology (Required Revenue). TNPA published port operational performance for 2017/2018 and 2018/2019 financial periods. The ports’ operational performance data assisted PRSA to select performance indicators to be considered for efficiency gains and the Ports Regulator published the first WEGO performance results in 2018/2019 financial period. The study applied both quantitative and qualitative research methods to analyse WEGO performance results. This study relies on secondary data published by PRSA. The author only focused to containers and Durban as the main container port of the country. This data shows performance scores for each KPI selected and the aim is to observe changes to performance and seek understanding behind improved or declined operational performance. However, there will be no specific statistical or mathematical models utilised. In conclusion, this research also offered recommendations on what TNPA and TPT can do to improve their performance and efficiency in order to be on par with their global counterparts

The synergistic effect of operational research and big data analytics in greening container terminal operations: a review and future directions

Container Terminals (CTs) are continuously presented with highly interrelated, complex, and uncertain planning tasks. The ever-increasing intensity of operations at CTs in recent years has also resulted in increasing environmental concerns, and they are experiencing an unprecedented pressure to lower their emissions. Operational Research (OR), as a key player in the optimisation of the complex decision problems that arise from the quay and land side operations at CTs, has been therefore presented with new challenges and opportunities to incorporate environmental considerations into decision making and better utilise the ‘big data’ that is continuously generated from the never-stopping operations at CTs. The state-of-the-art literature on OR's incorporation of environmental considerations and its interplay with Big Data Analytics (BDA) is, however, still very much underdeveloped, fragmented, and divergent, and a guiding framework is completely missing. This paper presents a review of the most relevant developments in the field and sheds light on promising research opportunities for the better exploitation of the synergistic effect of the two disciplines in addressing CT operational problems, while incorporating uncertainty and environmental concerns efficiently. The paper finds that while OR has thus far contributed to improving the environmental performance of CTs (rather implicitly), this can be much further stepped up with more explicit incorporation of environmental considerations and better exploitation of BDA predictive modelling capabilities. New interdisciplinary research at the intersection of conventional CT optimisation problems, energy management and sizing, and net-zero technology and energy vectors adoption is also presented as a prominent line of future research

An assessment of port productivity at South African container port terminals.

Master of Science in Maritime studies. University of KwaZulu-Natal, Westville 2015.The increasing intermodal sophistication and globalisation of the international container shipping industry, as well as increased competition on container throughput between major ports, requires container terminals to continuously improve their efficiency in relation to productivity and performance. This dissertation seeks to examine and analyse productivity data over a period of time, in order to determine port productivity trends at three main container terminals in South Africa. Given the existing infrastructure and available resources at the container port terminals, the research further analyses the gaps between expected or targeted performance against actual productivity trends to date. It further tests current performance levels against international benchmarks and makes recommendation on productivity optimisation and best practice. This study is motivated by the rapid development and a dire need in container terminal port operations to provide efficient and effective services as well as high port productivity. In South Africa, port productivity is still seen as suboptimal in global terms and it is for this reason that South African container terminals continue to seek improvement in achieving quicker port turnaround times. The literature review highlights thoughts and opinions on previous research as far as the formula for efficient and effective port productivity is concerned. When measuring port productivity, a number of factors need strategic integrations and a balanced approach. These include ship turnaround times, port superstructure performance, stowage plans, labour dynamics, information flow between various stakeholders, yard management and cost of operations. This research identifies crane performance and ship work-rate performance as the major indicators of productivity at the respective terminals. In the South African port terminals context, these two indicators were lower than targeted for. This is due to a number of reasons including lack of the full utilization of the current crane regime, equipment downtime, poor coordination between the operator and shippers, inefficient landside operations as well as labour inefficiency. This study therefore recommends that the port terminal operator should put the current infrastructure into full utilization, adhere to maintenance schedules of all terminal equipment with improved training regimes within a more skilled labour force. There is a need to enhance landside capacity and layout. This research contends that this would contribute towards shorter port stays and improved vessel turnaround times

The impact of automation on the efficiency and cost effectiveness of the quayside and container yard cranes and the selection decision for the yard operating systems

This research evaluates the impact of automated and semi-automated devices on the process of loading, discharging, stacking and un-stacking of containers using Quayside Cranes (QSCs), Straddle Carriers (SCs), Rubber Tyred Gantry cranes (RTGs) and Rail Mounted Gantry cranes (RMGs) in container terminals. The emphasis of study is on the assessment of performance and cost effectiveness of the existing automated quayside and yard cranes. The study in this thesis examines the economic implications of reducing QSCs' cycle-times brought about by automatic features installed on the post-Panamax cranes. It demonstrates that a considerable increase in the productivity of QSCs is related directly or indirectly to an expected reduction of crane cycle-times. The concept offered by the proposed improvements distinguishes between the traditional system of loading and discharging of containers and the automated methods. It implies that automation devices installed on conventional QSCs significantly reduce the total turnaroundtime and hence the cost of containerships' waiting-times. It argues, however, that there should be a balance between the cost of containerships' waiting-times and the cost of automated berths' unproductive-times (idle-times). This study uses the elements of queuing theories and proposes a novel break-even method for calculating such a balance. The number of container Ground Slots (GSs) and the annual throughput of container terminals expressed in Twenty-foot Equivalent Units (TEUs) have been used as the efficiency and performance measure for many years. The study in this thesis introduces appropriate container yard design layouts and provides a generic model for calculating the annual throughput for container terminals using semiautomated SC and RTG and automated and semi-automated RMG operating systems. The throughput model proposed in this study incorporates the dynamic nature, size, type and capacity of the automated container yard operating systems and the average dwell-times, transhipment ratio, accessibility and stacking height of the containers as the salient factors in determining a container terminal throughput. Further, this thesis analyses the concept of cost functions for container yard operating systems proposed. It develops a generic cost-based model that provides the basis for a pair-wise comparison, analysis and evaluation of the economic efficiency and effectiveness of automated and semi-automated container yard stacking cranes and helps to make rational decisions. This study proposes a Multiple Attribute Decision-Making (MADM) method for evaluating and selecting the best container yard operating system amongst alternatives by examining the most important operating criteria involved. The MADM method proposed enables a decision-maker to study complex problems and allows consideration of qualitative and qualitative attributes that are heterogeneous in nature. An Analytical Hierarchy Process (AHP) technique has been employed as a weighting method to solve the MADM problem. The AHP allows for the decomposition of decision problem into a hierarchical order and enables a pair-wise comparison of the attributes and alternatives. The results of the AHP analysis provide the basis for a pair-wise comparison, judgement and selection of the best automated or semi-automated container yard operating system