Application Of Intelligent Optimization Algorithm In Optimization Of Offshore Oil Exploration Route

In the project of offshore oil exploration,route optimization plays an important role in improving production efficiency and reducing production costs.The exploration route optimization can be regarded as a special case of the traveling salesman problem.Many scholars had solved the traveling salesman problem through various optimization algorithms.Intelligent optimization algorithm has been widely used in practical applications because of its simple principle,easy modeling and fast calculation speed.Firstly,the optimization principles of several intelligent optimization algorithms are studied,such as Genetic algorithm,Ant-colony algorithm,Simulate Anneal algorithm,Particle swarm optimization,Tabu search algorithm.And those intelligent optimization algorithms are programmed by C#.In the process of program implementation,the key parameters of intelligent optimization algorithm are tested,and the optimal parameters range suitable for offshore oil exploration route optimization is found.The five intelligent optimization algorithms are evaluated from three aspects: search results,search time and convergence speed.After study the several intelligent optimization algorithms,a hybrid intelligent optimization algorithm is proposed,which combine the advantages of Simulate Anneal algorithm and Tabu search algorithm.Through the simulation data and the past year operation project example data test,it is proved that the hybrid intelligent optimization algorithm has fast search speed,stabled search results,and can be used for offshore oil exploration route optimization.Finally,the optimized exploration route is used to generate thematic maps by using the GIS technology as an auxiliary tool for offshore oil exploration.