The offshore platform oil and gas processing system has a large number and complex types of equipment, and the pipe route design process relies on manual design, which has a long cycle, low efficiency, high cost, and is difficult to optimize globally. In this study, an intelligent pipe route design method is proposed using the improved ant colony optimization algorithm, MAACO. Firstly, a multi-strategies pipeline adaptive adjustment mechanism addresses the disadvantage of long search cycles in complex pipe route design and improves the problem of the algorithm easily getting stuck in local optimum during the search process. Subsequently, a semi-automatic state transition rule is introduced to enhance design efficiency and scheme quality. Perform simulation experiments on offshore platform pipe route design cases, and evaluate the proposed improved ant colony algorithm against the existing mature algorithms. The experimental results show that the pipe route design solution obtained by the proposed method is superior to the comparative algorithm in key indicators such as path length, number of bends. Finally, the proposed MAACO is utilized to solve engineering problems in offshore platform pipeline design, verifying its adaptability and optimization ability in complex pipe route design problems.