An iterative method, implemented by a computer, for optimally designing a system for monitoring a geographical area, comprising a plurality of sensors having different types and characteristics represented by a vector S, each component of which indicating the type and the characteristics of a sensor and its position in said area, said system having a plurality of absolute non-financial technical constraints that must be complied with the sensors of said system, said method comprising at least the following steps: ∘ a step of initialising said vector S to a solution So; ∘ a step of disrupting sensors making up the solution S n at the iteration of index n in order to obtain a new candidate solution S n+1 at the iteration of index n+1, said disruption causing the type or a characteristic of at least one of said sensors to be changed, the types of possible sensors also including a dummy type, the characteristics of which do not affect the overall cost of the solution S; ∘ a step of assessing the cost of said solution S n+1 based on a global cost function C that is determined as a combination of a plurality of sub-criteria C k for optimising at least one characteristic of said sensors that make up the solution S; ∘ a step of selecting the new current solution S n+1 at the iteration n+1 on the basis of a transition probability P transition = η ( C ( S n), C ( S n +1)) that decreases as a function of ( C ( S n +1) - C ( S n)), leading to the selection of the new candidate solution S n+1 = S n+1 or to the preservation of the preceding solution S n+1 = S n; ∘ a step of storing, upon each iteration, the best solution S best that is obtained, which verifies the following relation: if C S n + 1 < C S best, S best = S n + 1; ∘ a step of testing the termination or the continuation of the iterations of said method; ∘ a final step, when said testing of termination is positive, of producing the optimal solution S best that contains the number, the type, the characteristics and the position of the sensors that are adapted to monitor said geographical area. ∘ a step of initialising said vector S to a solution So; ∘ a step of disrupting sensors making up the solution S n at the iteration of index n in order to obtain a new candidate solution S n+1 at the iteration of index n+1, said disruption causing the type or a characteristic of at least one of said sensors to be changed, the types of possible sensors also including a dummy type, the characteristics of which do not affect the overall cost of the solution S; ∘ a step of assessing the cost of said solution S n+1 based on a global cost function C that is determined as a combination of a plurality of sub-criteria C k for optimising at least one characteristic of said sensors that make up the solution S; ∘ a step of selecting the new current solution S n+1 at the iteration n+1 on the basis of a transition probability P transition = η ( C ( S n), C ( S n +1)) that decreases as a function of ( C ( S n +1) - C ( S n)), leading to the selection of the new candidate solution S n+1 = S n+1 or to the preservation of the preceding solution S n+1 = S n; ∘ a step of storing, upon each iteration, the best solution S best that is obtained, which verifies the following relation: if C S n + 1 < C S best, S best = S n + 1; ∘ a step of testing the termination or the continuation of the iterations of said method; ∘ a final step, when said testing of termination is positive, of producing the optimal solution S best that contains the number, the type, the characteristics and the position of the sensors that are adapted to monitor said geographical area.