Probabilistic Parameter Control Method and Evolutionary Optimization of WASP Building Floor Plan Generation Algorithm

Modular construction and digital manufacturing technologies are increasingly prevalent in contemporary architectural design. The WASP (Wasp Aggregate Spatial Production) algorithm for designing and manufacturing discrete components has been applied to digital manufacturing product exploration, game development, and layout studies in urban planning and architectural design. However, challenges remain in setting connection rule parameters when applying WASP to architectural layout exploration. Different architectural design requirements necessitate extensive adjustments to WASP's connection rules, which reduces the algorithm's practicality. This work proposes a control and optimisation method for the WASP algorithm. It generates planar layouts using the WASP algorithm with rule application probability parameters. It guides the genetic algorithm (GA) to dynamically adjust spatial combination rules through a spatial combination efficiency evaluation system based on spatial proximity relationships. This method simplifies the adjustment process of WASP connection rules and enhances the controllability of the WASP algorithm through rule application probability parameters. This approach provides architects with more suitable reference solutions in the early design stages.