Transportation problem is an optimization problem. In general, it was studied under random or uncertain condition. Considering the recent complexity, it is not enough to make should be a perfect transportation plan only based on. Usually, there is not only uncertainty but also randomness in many systems. In this paper, the aim is to investigate a transportation problem under uncertain and random environment. As a result, a conceptual uncertain random model is proposed for the problem, where the supplies are considered as random variables, and the costs and the demands are uncertain variables. By minimizing the expected value of uncertain objective function and taking confidence levels on constraints, transforming the model into a crisp mathematical form is the main conclusion. By minimizing the expected value of uncertain objective function and taking confidence levels on constraints, the above model can be turned to a mathematical form. Then transforming the model into a typical mathematical programming model is the main conclusion by using uncertainty theory and probability theory. At the end, a numerical example is given to show the feasibility of the model.

This paper unveils the strong competition in container cargo between Hong Kong Port which has been emerging as an international maritime center since the 1970s and Shenzhen Port which has recently gained remarkable achievements in the Pearl River Delta region. Among various competing strategies, the study focuses on the long-term one in which two ports will decide to compete by investing in capacity. The purpose of this research is to examine their decision, making process and to suggest future strategic actions in the current situation. Within its scope, only economic profit brought back from the investment is considered. For this reason, an uncertain payoff two-person game model is developed where an uncertain factor of demand is involved. In applying Uncertainty theory (Liu, 2013), the two methods to solve the game are introduced, including uncertain statistics and the expected Nash Equilibrium strategy. The results obtained from this research generate meaningful suggestions for future competition plan for the two selected ports, which conclude that Shenzhen is the dominant port in this long-term strategy. Compared to existing works on the same topic, the paper shows its distinctiveness by studying the latest competitive situation with regard to the uncertain demand in the game model.

In the tanker industry, there are a lot of uncertain conditions that tanker companies have to deal with.For example, the global financial crisis and economic recession, the increase of bunker fuel prices and global climate change. Such conditions have forced tanker companies to change tankers speed from full speed to slow speed, extra slow speed and super slow speed. Due to such conditions, the objective of this paper is to present a methodology for determining vessel speeds of tankers that minimize the cost of the vessels under such conditions. The four levels of vessel speed in the tanker industry will be investigated and will incorporate a number of uncertain conditions. This will be done by developing a scientific model using a rule-based Bayesian reasoning method. The proposed model has produced 96 rules that can be used as guidance in the decision making process. Such results help tanker companies to determine the appropriate vessel speed to be used in a dynamic operational environmental.

According to the statistics of the last five years, fishing vessel accidents accounted for about 80% of collisions of all ships and has led to many casualties. To prevent collision accidents, it is important to assess the collision risk potential related to the sailing characteristics of fishing vessels. The authors represented the traffic patterns of vessels that sail around Wando waters based on Automatic Identification System (AIS) and Radio Detecting and Ranging (RADAR) data. The authors analyzed the statistical near miss data between fishing vessels and non-fishing vessels in the Wando Vessel Traffic Services (VTS) area and assessed the risk of ship collisions. From this research, the authors identified waters with a high risk of ship collisions. The analyzed results can be used as basic data to develop collision prevention strategies which aides the decision making and efficient operation of VTS officers (VTSO.)

This paper presents a study of the port logistics activities at the port of Santos (Brazil). The study follows a qualitative approach and it is based on in-depth interviews with some key actors from Santos port logistics chain. Based on these interviews, the main dysfunctions and improvement opportunities associated to the container port logistics processes at Santos were identified. The results show that the main dysfunctions are related to the existing information flows. Due to this, a new information flow related to the studied port is proposed and some probable results of the implementation are identified. The findings contribute both to the studied port and to the academic community, as the number of studies addressing port logistics activities is still limited.

The shortest path problem is one of network optimization problems. This paper considers a shortest path problem under the situation where lengths of arcs in a network include both uncertainty and randomness, and focuses on the case that the lengths of arcs are expressed by uncertain random variables. This paper presents a new type of model: relative entropy model of shortest path. By the definition of relative entropy of the uncertain random variables, relative entropy model of shortest path problem is proposed to find the shortest path which fully reflects uncertain and random information. This model is formulated to find a shortest path whose chance distribution minimizes the difference from the ideal one. A numerical example is given to illustrate the model’s effectiveness.