Metaheuristic Algorithm and Laser Projection for Adjusting the Model of the Last Lower Surface to a Footprint

Area of Science:

• Computational geometry
• Bio-inspired computing
• Manufacturing engineering

Background:

• Custom shoe last manufacturing relies on accurate lower-surface models.
• Computational algorithms are used to adjust these models to specific foot shapes.
• Optimization of last lower-surface models is crucial for custom fit.

Purpose of the Study:

• To implement a nature-inspired metaheuristic algorithm for adjusting last lower-surface models.
• To adapt the last lower-surface model to precise footprint topography.
• To enhance the accuracy and efficiency of custom shoe last production.

Main Methods:

• A metaheuristic genetic algorithm was employed for surface model adjustment.
• An objective function was defined using the last lower Bezier model and footprint topography.
• A mean error function guided the optimization process within a deduced search space.

Main Results:

• The genetic algorithm successfully optimized the Bezier surface model for the last lower surface.
• The adjusted surface closely matched the recovered footprint topography.
• Enhanced precision in the last lower-surface adjustment was achieved.

Conclusions:

• Metaheuristic algorithms, specifically the genetic algorithm, are effective for optimizing last lower-surface models.
• This method improves the accuracy of custom last manufacture by adapting models to footprint topography.
• The study highlights the potential of nature-inspired algorithms in footwear engineering.