The Optimization Research Of Charter Bunkering Replenishment Based On Genetic Algorithm

Transportation is the foundation of the national economy. The effective use of transportation can make the materials transported to areas, in which the participants can get the highest value. On the macro level, Transportation also plays a key role in the optimal allocation of resources. Marine transportation mode accounts for more90%during the global transportation system, which means international shipping industry plays a fundamental role to the development of the world economy and the trade. The tramping service, particular the chartering service, together with the container liner shipping, contributes to the process of the global marine transportation.In the marine chartering market, there exists some main chartering types such as voyage charter, time charter, time charter on trip basis (TCT) and etc. Particularly, a special chartering business mode as follows is very popular: ship operator rents a vessel from the head-owner in TCT way to become a disponent owner, meantime, rent out the vessel to the charterer in voyage charter mode who has the freight demands in the market. As for this kind of chartering mode, on one hand the ship operator is the charterer who need to pay the hire to the head-owner, on the other hand, he acts as disponent owner and earns the freight from the charter whose cargo are shipped. Some matter need to notice is, during the voyage chartering, ship operator needs to be responsible for the fuel cost, which is the significant part of the total cost, and moreover, whether he can control the fuel cost reasonably will directly decide the size of the profit space. Therefore, it is necessary and urgent to analyze and optimize the vessel fuel replenishment planning for the ship operator.This paper attempts to analyse the concerned factors which effect the voyage revenue and fuel replenishment under this chartering mode, and further formulates a fuel replenishment optimization model with objective of maximizing total voyage revenue. Meanwhile, by specially considering the characteristics and nature of the problem can be concluded as the Combination of Knapsack Problem and Allocation Problem, a specific heuristic genetic algorithm is developed and used to solve the mathematic model. Finally, the paper introduces some real chartering and shipping cases which contain raw and valid data, and by the calculations of the model and algorithm developed above, the cases get the optimal fuel replenishment plan with max revenue, verifying the validity and feasibility of the model and genetic algorithm. Meantime, it is clear that the analysis about the fuel replenishment optimization of this paper can guide the marine companies’business activities to some extent to control the fuel cost to improve the profit space and the market competitiveness.