Poverty is closely related to the problem of unequal distribution of basic needs across regions. To address this challenge, graph theory provides a rigorous framework for designing efficient distribution networks that ensure accessibility while minimizing cost. In this work, we examine the dominant metric dimension, explained as the smallest possible size of a set that is both resolving and dominating. The primary finding shows that for the graph formed via the rooted product G ∘ 𝓗, this dimension aligns to the sum of the dominant metric dimensions of all graphs within the family 𝓗. When the sequence consists of complete graph, star graph, and complete bipartite graph with the rooted vertex at a pendant, the result should be reduced by n. These findings provide insight into how the number of distribution centers can be optimized in various network structures. From the perspective of poverty alleviation, this result implies that efficient placement of distribution hubs can reduce infrastructure costs while ensuring that every community is within reach of essential goods. This paper determines the dominant metric dimension of the specified product G ∘ 𝓗, represented as Ddim(G ∘ 𝓗). The findings indicate that the value of Ddim(G ∘ 𝓗) depends on the structural properties of the graphs within the sequence 𝓗. When 𝓗 consists of rooted cycle graphs, rooted star graphs, and rooted path graphs, the dominant metric dimension of G ∘ 𝓗 is equal to the total sum of the dominant metric dimensions of each element in 𝓗. On the other hand, when H consists of rooted complete graph, Ddim(G ∘ 𝓗) is the sum of their individual dominant metric dimensions, each reduced by one.