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Most manufacturing companies have tested and adopted sustainable design methods to navigate their product's environmental transition. While successful at first in enhancing their environmental performance, these companies later struggle to pursue their environmental transition. This entails mastering two critical competencies: identifying transition unknowns, and fostering adequate design efforts. This action research with an innovative design intermediary - which has completed four sustainable packaging missions - reveals the specific design barriers encountered for environmental transition. [ABSTRACT FROM AUTHOR]

Generative Design (GD) is a design approach that uses algorithms to generate designs. This paper investigates the role of optimisation algorithms in GD process. We study how Pareto Fronts – a classical optimization algorithm output – help designers to browse the variety associated with a design problem. Thanks to the "splitting condition" from design theory, we show that valuable Pareto Fronts for designers are those that allow the exploration of a variety of design parameters without modifying substantially the performance of the designed solution. We call "Splitting Pareto Front" the Pareto Fronts that display this property and investigate how to generate them. We compare, on an electrical battery design problem, two optimization algorithms – NSGA-II and MAP-Elites – based on the design parameters variety they generate. Our results show that MAP-Elites generates Pareto Fronts that are more splitting than those generated by NSGA-II. We then discuss this result in term of the design process: which algorithm is best suited for which design task? We conclude with the importance for future research on Generative Design Algorithms (GDA) to study jointly the functioning of GDA and their expected contribution to the design process. [ABSTRACT FROM AUTHOR]