Abstract

Creating functional midsoles for shoes is a challenging task that involves considering different aspects such as stability, comfort, manufacturability, and aesthetics. No single approach exists to design a midsole that meets all these objectives effectively. Therefore, this study aims to introduce a multidisciplinary optimization method to develop custom shoe midsole structures. The proposed approach involves utilizing tetrahedral mesh generation to generate diverse structures and leveraging swarm intelligence to search for optimal designs. Tetrahedral mesh generation is used to create midsole structures because tetrahedral structures are renowned for their exceptional strength. Additionally, tetrahedral mesh generation is a well-established tool that provides the added advantage of fully automatic construction for complex shaped midsoles. By adjusting the mesh generation parameters, a wide range of solutions can be generated that meet multiple objectives. To enhance the swarm’s exploration of the design space and discover more local optima, a new swarm behavior is developed that promotes diversity. Furthermore, a quantitative measurement tool is created to evaluate various objectives. In order to test the effectiveness of the generative approach, the midsoles obtained from the design exploration are analyzed that performed the best and the worst in relation to each objective. The findings revealed a substantial difference between them, with scores differing by two to four times. Additionally, when compared to other lattice structures, the tetrahedral midsole structure created by the proposed method demonstrated superior compliance with the foot and better redistribution of plantar stress. This makes it an ideal candidate for use in shoe midsoles. The multidisciplinary optimization technique proposed here is a valuable resource for engineers and designers in the footwear industry, allowing them to develop high-performance midsole structures that meet the needs
of both consumers and athletes. Furthermore, this method can be applied to optimize other complex structures in various industries, such as civil, automotive, and aerospace engineering