Recursive expected conditional value at risk in the fleet renewal problem with alternative fuel vehicles.

We study the fleet portfolio management problem faced by a firm deciding which alternative fuel vehicles (AFVs) to choose for its fleet to minimise the weighted average of cost and risk, in a stochastic multi-period setting. We consider different types of technology and vehicles with heterogeneous capabilities. We propose a new time consistent recursive risk measure, the Recursive Expected Conditional Value at Risk (RECVaR), which we prove to be coherent. We then solve the problem for a large UK based company, reporting how the optimal policies are affected by risk aversion and by the clustering for each type of vehicle

Optimization in container liner shipping

We will give an overview of several decision problem encountered in liner shipping. We will cover problems on the strategic, tactical and operational planning levels as well as problems that can be considered at two planning levels simultaneously. Furthermore, we will shortly discuss some related problems in terminals, geographical bottlenecks for container ships and provide an overview of operations research methods used in liner shipping problems. Thereafter, the decision problems will be illustrated using a case study for six Indonesian ports

Efficiency optimization of the transportation supply chain activity: the maritime option for Volkswagen Autoeuropa

Field Lab of Entrepreneurial Innovative VenturesWith the current pressures for companies to reduce their CO2 emissions levels and the worldwide competition more fierce than ever it becomes critical for companies to optimize their processes and improve supply chain efficiency. Develop solutions that could satisfy both these requirements is mandatory to improve and sustain today’s businesses. For Portuguese industries with high transportation costs the maritime option has become increasingly reliable, experiencing a huge structural and technological improvement in the past decades. This work project aims the study of maritime transportation feasibility for Volkswagen Autoeuropa company; it combines the strong theoretical background with a data analysis and multi-scenario assessment. The methodologies used were the billing analysis, at the beginning, then followed by a thorough analysis of transportation and inventory costs and volumes which led to a range of potential supplies to be transported by maritime. At the end the result was 3 possible routes which demonstrate after the analysis only one be a viable option. It was performed also a CO2 analysis, a risk analysis and consequent contingency plan in order to finalize a complete approach to this maritime projectNSBE - UN

Evolutionary fleet sizing in static and uncertain environments with shuttle transportation tasks - the case studies of container terminals

This paper aims to identify the optimal number of vehicles in environments with shuttle transportation tasks. These environments are very common industrial settings where goods are transferred repeatedly between multiple machines by a fleet of vehicles. Typical examples of such environments are manufacturing factories, warehouses and container ports. One very important optimisation problem in these environments is the fleet sizing problem. In real-world settings, this problem is highly complex and the optimal fleet size depends on many factors such as uncertainty in travel time of vehicles, the processing time of machines and size of the buffer of goods next to machines. These factors, however, have not been fully considered previously, leaving an important gap in the current research. This paper attempts to close this gap by taking into account the aforementioned factors. An evolutionary algorithm was proposed to solve this problem under static and uncertain situations. Two container ports were selected as case studies for this research. For the static cases, the state-of-the-art CPLEX solver was considered as the benchmark. Comparison results on real-world scenarios show that in the majority of cases the proposed algorithm outperforms CPLEX in terms of solvability and processing time. For the uncertain cases, a high-fidelity simulation model was considered as the benchmark. Comparison results on real-world scenarios with uncertainty show that in most cases the proposed algorithm could provide an accurate robust fleet size. These results also show that uncertainty can have a significant impact on the optimal fleet size

Modelling the impacts of uncertain carbon tax policy on maritime fleet mix strategy and carbon mitigation

The maritime transport industry continues to draw international attention on significant Greenhouse Gas emissions. The introduction of emissions taxes aims to control and reduce emissions. The uncertainty of carbon tax policy affects shipping companies’ fleet planning and increases costs. We formulate the fleet planning problem under carbon tax policy uncertainty a multi-stage stochastic integer-programming model for the liner shipping companies. We develop a scenario tree to represent the structure of the carbon tax stochastic dynamics, and seek the optimal planning, which is adaptive to the policy uncertainty. Non-anticipativity constraint is applied to ensure the feasibility of the decisions in the dynamic environment. For the sake of comparison, the Perfect Information (PI) model is introduced as well. Based on a liner shipping application of our model, we find that under the policy uncertainty, companies charter more ships when exposed to high carbon tax risk, and spend more on fleet operation; meanwhile the CO2 emission volume will be reduced

Simulation modelling of chief officers’ working hours on short sea shipping

Short sea shipping poses significant problems for many seafarers, particularly for officers employed in oil tankers as chief officers. This study examines chief officers’ working conditions on short sea shipping. In this study, Simio simulation software was utilised to evaluate the working hours of chief officers. The results demonstrate that the rest periods of the chief officers have been less compromised as the navigation period increases in oil tankers operated on short sea shipping. To comply with the relevant regulations, a navigation period of 24–28 h is the minimum condition for an oil tanker to have a chief officer; however, an additional officer may be required for shorter voyages. The findings of the research provide some recommendations to maritime authorities to achieve safe short sea shipping

Risk control in maritime shipping investments

In this paper we extend the state-of-the-art stochastic programming models for the Maritime Fleet Renewal Problem (MFRP) to explicitly limit the risk of insolvency due to negative cash flows when making maritime shipping investments. This is achieved by modeling the payment of ships in a number of periodical installments rather than in a lump sum paid upfront, representing more closely the actual cash flows for a shipping company. Based on this, we propose two alternative risk control measures, where the first imposes that the cash flow in each time period is always higher than a desired threshold, while the second limits the Conditional Value-at-Risk. We test the two models on realistic test instances based on data from a shipping company. The computational study demonstrates how the two models can be used to assess the trade-offs between risk of insolvency and expected profits in the MFRP