Abstract
This study proposes and tests methods for computational multi-objective optimization (MOO) for circular economy (CE) product design. Current CE design frameworks and assessments fail to address two key areas in which computational optimization can add value: identifying the best-performing solutions among many options and managing multiple potentially conflicting or redundant CE objectives. Furthermore, effective optimization methods for CE design can improve the outcomes of manual design processes, resulting in reductions in waste and environmental impacts for products throughout their lifecycles. This paper provides an overview of instances where computational optimization can provide the greatest value within CE product design frameworks and methods for converting circular design strategies to a simplified set of optimizable objectives for MOO. These methods were tested to optimize a product design case study. The results demonstrate the improvements MOO can achieve for CE product design and provide a basis for discussion of future work.
•Optimization methods for circular economy (CE) product design.•Current circular design frameworks lack computational optimization methods.•Evaluation of circular design strategies for the applicability of optimization.•Multi-objective optimization (MOO) identifies conflicting circularity objectives.•Demonstrates optimization of the product design case study for CE.