A Framework for Enhancing User Experience in Existing Exhibit Spaces Using Evolutionary Algorithms

Abstract

Believing that the direct beneficiaries of any architectural space are the users and so designing and developing a new user-centric approach is mandatory. This approach is applied by using manual tracking and observations to examine visitor parameters such as visitors’ circulation, visiting styles, visibility patterns, active engagements and interaction with exhibits and spatial configuration developments. This thesis aims at analysing the exhibition configuration and extracting the solid and valid parameters for both spatial and visitor’s parameters which are (ill-defined) and transform them to (well-defined) inputs in the Evolutionary Algorithm component. Developing a method to solve the complexity of the spatial problem and getting the optimum result of the maximum visible area on the circulation curve and the percentage of the visible exhibits in order to be able to get a better probability of the enhancement.