Elaboration of the equipment replacement terms taking into account wear and tear and obsolescence

At present, shipowners have to take active measures to improve the efficiency of their fleet to remain competitive on the freight market. In this respect, the development of a shipping company’s fleet is immensely important due to the ability of such vessels to operate with maximum efficiency and flexibility when the structure of cargo flow is heterogeneous. At the same time, fuel expenses account for a considerable part of shipping company expenses. Fuel consumption greatly depends on ship speed. Therefore, the efficiency of maritime shipping can be greatly increased by choosing optimal speed. The purpose of this research is to develop a methodology for justifying the selection of shipping company fleet expansion projects based on cargo flow structure characteristics, considering the possibility of slow steaming ship operation. Net Present Value and Profitability Index were taken into account to compare the efficiency of acquisition and operation projects pertaining to ships with significantly different deadweight and market values.

The main aim of the article is to develop technique for determining the optimal equipment of a sea grain terminal with technical means at the stage of its design. In many works, in order to study the performance of transport systems operating under conditions when the loading level is subject to random fluctuations, the queuing theory methods and random processes are used. However, in a number of cases this approach does not allow to take into account all specifics of the processes that significantly affect sea terminals performance. Also, most of the available studies aim at enhancing a certain single key performance indicator (it can be total costs, performance, income, etc.) to its maximum, provided that the other indicators are within the permissible range of values. However, in many cases, there are more than one key performance indicator which need to be improved. Since the queuing theory and single criterion optimization methods did not allow to achieve the desired results, to study the problem, a technique was introduced based on the combination of simulation modelling and multicriteria optimization methods, which allows us to take into account all the main features of operations at grain terminals. To assess the terminal economic efficiency, the Equivalent Annual Cost indicator was used. The relationship between the cargo unit transshipment cost and the average processing time of consignments is analyzed, provided that the cargo flow intensity is subject to random fluctuations. Using this relationship, a technique for determining the optimal composition of grain terminal equipment was introduced, based upon the multicriteria optimization and simulation modelling methods. The developed technique makes it possible to determine the qualitative and quantitative choice of equipment for a sea grain terminal, taking into account both the cargo transshipment cost and the processing time of consignments. The studies have shown that, with an appropriate choice of the terminal equipment, it is possible to significantly reduce the time of cargo handling due to only a slight increase in the cargo unit transshipment cost.

We consider a problem of minimizing the maritime cargo delivery route length to reduce the delivery cost. In our model, the cost is equivalent to the sum of tour lengths of feeders used for the delivery to cover the route. Formulated as a multiple tr...

The problem of minimizing the cost of maritime cargo delivery is considered. The cost is equivalent to the sum of the tour lengths of feeders used for the delivery. The problem is formulated as a multiple traveling salesman problem. In order to find its solution as the shortest route of the tours of feeders, a genetic algorithm is used where we present two inequalities constraining the tour length of every feeder to lie between the shortest and longest lengths. Apart from the constant tour constraint violation penalty in the genetic algorithm, we suggest a changeable penalty as an exponential function of the algorithm iteration, where we maintain the possibility of the penalty rate to be either increasing or decreasing, whose steepness is controlled by a positive parameter. Our tests show that the changeable penalty algorithm may return shorter routes, although the constant penalty algorithms cannot be neglected. As the longest possible tour of the feeder is shortened, the changeable penalty becomes more useful owing to a penalty discount required either at the beginning or at the end of the algorithm run to improve the selectivity of the best feeder tours. In optimizing maritime cargo delivery, we propose to run the genetic algorithm by the low and constant penalties along with the increasing and decreasing penalties. The solution is the minimal value of the four route lengths. In addition, we recommend that four algorithm versions be initialized by four different pseudorandom number generator states. The expected gain is a few percent, by which the route length is shortened, but it substantially reduces expenses for maritime cargo delivery.

SThe dynamic model of change in the performance indicators of sophisticated equipment was proposed. The proposed model consists of two parts. The first part concerns modeling of a random process of changes in the level of equipment loading and is described by the stochastic equation in the form of Ito (5). The second part concerns modeling of dynamics of equipment wear depending on changing in the levels of its loading and is described by the differential equation. As a result, the stochastic dynamic model of changes in performance indicators of sophisticated equipment, which takes into account random fluctuations of equipment loading, was obtained. Using the proposed model, we analyzed dynamics of average total specific costs of equipment in the case when a degree of equipment loading is subject to random changes. Quantitative ratios of average total specific costs of equipment, level of fluctuations of these costs during possible random changes in loading and terms of equipment replacement were established. Studies have demonstrated that changes in average total specific costs of equipment can be insignificant for a certain time. In this case, the spread range of the level of costs of equipment within the same time range can increase significantly. That is why it makes sense to reduce the service term of equipment. This would lead to an insignificant increase in the mean values of equipment performance indicators, however, their stability level will improve considerably.