Generative and Evolutionary Design Exploration intends to reflect on the interaction between design exploration and evolutionary design optimisation.

Expert designers, both architects and engineers, typically display a strategy of exploring design alternatives, albeit a relatively small number. Expert architects’ strategy in problem solving has been denoted breadth first, depth next; in comparison to novices, who typically display less breadth of exploration. While engineers’ strategy is markedly different, design alternatives play a role as importantly, if not more. Where designers typically consider a very small number of alternatives in their work, this can be explained by cognitive limits, opening the door for computational support of design exploration. In particular, It has been argued that exploration is a compelling model for designer action and that designers benefit from tools that amplify their abilities to represent goals and problems spaces, and to search for designs.

Generative and evolutionary methods have proven to be strong catalysts for design exploration and design optimisation has served as a means to assist in this exploration. Recently there is a marked move towards using optimisation to aid exploration. Optimisation is rarely intended to yield an optimal solution per se, instead assisting in gaining insight in the solution space, thereby reducing the size of the solution space for exploration, possibly focusing attention towards the Pareto boundary. Even at the Pareto boundary there are a large number of solutions worthy of further exploration. Hand in hand, exploration and optimisation lead to a better understanding of the complexities of design issues and help designers in their decision-making process, especially with multi-objectives problems, which is a nature of many design problems. As such, the focus of attention in generative and evolutionary design is shifting from the techniques themselves, and their direct application, to the way we are using these techniques to assist and improve the design and engineering process.

We might frame generative and evolutionary design from the point of view of a “conversation”; nothing uncommon for generative design, though it is for optimisation. This type of conversation is between the designer (or design team) and the computer, and is digitally enhanced. As such, the aim is less on optimisation per se and more on exploration—the results from optimisation are about changing one’s way of thinking more than choosing a single design and then realizing it. We can then ask the question of how these types of conversation can unfold—how do they start and where do they end? What to do with thousands of similar solutions?

We invite submissions that address generative and evolutionary design exploration and contribute to the discussion of the interaction between design exploration and evolutionary design optimisation.

Information about the format and style required for AIEDAM papers can be found at http://aiedam.usc.edu/index.php/Authors/ForAuthors.

However, note that all inquiries for special issues go to the Guest Editors, and not to the Editor in Chief.

Important dates: 

Intend to submit (Title & Abstract):

As soon as possible

Submission deadline for full papers:

15 September 2014

Reviews due:

15 December 2014

Notification and reviews due to authors:

15 January 2015

Revised version submission deadline:

16 March 2015

Issue to Publisher:

1 June 2015

Issue Appears:

Fall 2015

Guest editors:

Dr. Rudi Stouffs

Dr. Yaqub Rafiq

Department of Building Technology

School of Marine Science and Engineering

Faculty of Architecture

Faculty of Science & Environment

Delft University of Technology

Plymouth University

2600 GA Delft, The Netherlands

Rm 21, Reynolds, Drake Circus, Plymouth, Devon, PL4 8AA, UK

Email: r.m.f.stouffs @ tudelft.nl

Email: m.rafiq @ plymouth.ac.uk