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Over the last decade the concept of ‘Regenerative Design and Decision-Making’ has been introduced as a mind-set which considers the integration of all humans’ activities and natural systems, in a broader vision than the classic concept of ‘Sustainability’ (mostly focused on the present). This vision identifies a greater scope, considering ‘Regenerative’ as a package of ‘sustainable for today’, ‘sustainable for future’, and ‘heal the past’. The ‘system evolutions’ and uncertainty of changes, are key factor to be considered in designing of required infrastructures of sustainability for future and healing the damages to the economy, society and environment in the past. this in turn, highlights the role of ‘Evolution Analysis (EA)’ and ‘Future Identification (FI)’ in regenerative developments. A practical solution for FI is to develop EA algorithms, to be applied to identify the rates of changes over the integrating flows, through projects’ time-frames in a more precise way. This in turn, saves huge rates of resources through design and implementation of extra infrastructures, to deal with future changes; as well as supporting the decision-makers to reach more realistic solutions, with higher levels of precision. This paper focuses on a real case-study, the Faculty of Art and Architecture campus, in Shiraz University, Shiraz, Iran, as a part of an evolution analysis research project, sponsored by ‘Iran’s National Elites Foundation’, and the solutions to deal with the real-projects’ limitations, such as disorganisation/lack of History Data (HD), stored by different teams over a ten-year period of the campus history. Such limitations, are principally caused by ‘changes in management systems’, as a key integrating flow in systems’ lives, and cause of uncertainties in FI. Indeed, the paper demonstrates some critical and practical solutions, to develop EA algorithms for Regenerative Design and Decision-Making in real practices. © 2018 The Authors. Published by Diamond Congress Ltd. Peer-review under responsibility of the scientific committee of the Creative Construction Conference 2018.

Developing of evolution analysis algorithms in regenerative design and decision-making; Demonstrated through a case study in Shiraz, Iran