An evolutionary strategy enhanced with a local search technique for the space allocation problem in architecture, Part 1: methodology

Abstract

The drafting of floor plans is mostly hand made in today’s architectural design process. The use of computerized floor planning techniques may enhance the practitioner’s range of solutions and expedite the design process. However, despite the research work that has been carried out, the results obtained from these techniques do not convince many practitioners to accept them as part of their design methods. The existing literature shows that every research approach is different in the way in which architectural space planning is tackled. Consequently, each approach tends to be too specific or too abstract.

The Space Allocation Problem in architecture may be stated as the process of determining the position and size of several rooms and openings according to the user’s specified design program requirements, and topological and geometric constraints in a two-dimensional space.

This is the first part of a paper that describes an enhanced hybrid evolutionary computation scheme that couples an Evolutionary Strategy (ES) with a Stochastic Hill Climbing (SHC) technique to generate a set of floor plans to be used in the early design stages of architectural practice. It presents the mathematical model with the problem statement and how the individuals’ fitness is computed, the implemented methodological approach, how the adaptive operators are implemented, the summary of the overall procedure, and conclusions.