Environmentally friendly practices in the architecture engineering and construction (AEC) industry are embraced as never before due to the crucial need for a more sustainable future. This paper presents a novel algorithmic approach by focusing on the possible cycle usage of concrete wall segments in the AEC; motivated by the idea of “Reusing instead of Recycling”. The traditional structural engineering practice rarely considers the cyclic usage of such elements; not only due to legal and logistical reasons but also due to the enormous time effort in deciding how to determine the best layout for reusable elements within a predefined structural geometry. To address this research question, a novel computational methodology is described in this paper, incorporating a developed tool, parametric modeling, and structural multi-objective optimization (MOO). The methodology interprets the planned geometry of the building as a fixed metric quantity, in which the evolutionary generative algorithm finds optimal places for the reusable wall segments (R-walls). Thus, the optimization goals are focused on 1) minimizing the cut waste of R-walls due to remaining non-fitting parts, and 2) minimizing the needed new concrete mass. Two test cases were carried out within this research: 1) a test case with very simple a multi-storey rectangular geometry and 2) a test case with a realistic geometry of a residential multi-storey building sketched within the 4D semantic mixed reality sketching tool MR-Sketch. The results indicate the efficiency of the proposed methodology and of the developed tool. Summarized, this paper presents a generative computational pipeline of the layout´s optimization for reusable reinforced concrete walls, highlighting the potential for environmental benefits. However, the integration of these practices into today’s AEC sector necessitates the collaboration among structural and mechanical engineers, innovative companies for reusable bearing elements, and the necessary legal framework.