Subsea flexible pipelines removal is subject to order restrictions, mostly caused by crossings. It is proposed to create a computational algorithm to design an optimal order of vessel intervention over a field. A real field was studied, and, from it, the mathematical base model was created upon graph theory, with great correlation with the minimum feedback arc set problem. Vessel movements were discretized and reduced to removal, reposition, and cut, leading to a state search. A-star algorithm was implemented to guide the search for the solution. Then, the complete algorithm was built, tested in a minimal environment, and finally applied to the real instance. To improve performance, a beam search filtering was envisioned, using seven ranking functions. Constructed model is suspected to be NP-hard, by correlation to minimum feedback arc set problem, leading to a large space search. Instances containing under 100 crossings were solved optimally, without needing any assistance. After implementing the heuristics and beam search, solution time was lowered by about 20 times, demonstrating the effectiveness of the technique. Also, ranking functions for pipe repositioning based on crossing count led to better results than crossing density. For cutting, an approximation based on feedback arc set was used. GreedyFAS was employed and gave satisfactory results. Bigger instances containing around 3000 crossings could not be solved optimally in a reasonable time, even with the heuristics. Improvements in A-star estimation function and bound the solution branches might lead to an optimal solution for these larger instances. Model proposed simplifies the operational order decisions and helps build the scheduling of operations. As it is based on state search, other aspects in logistics, vessel capacities and steps in decommissioning processes may be added, adjusting the neighboring weights and branching, keeping the same core.