Revisiting Non-Convexity in Topology Optimization of Compliance Minimization Problems
Mohamed Abdelhamid, Aleksander Czekanski

TL;DR
This paper analyzes the sources of non-convexity in topology optimization for compliance minimization, emphasizing the dominant role of density penalization and advocating continuation methods to find global optima.
Contribution
It provides a comprehensive mathematical analysis of non-convexity sources, especially highlighting the effects of penalization and filtering in density-based topology optimization.
Findings
Penalization of intermediate densities is the main cause of non-convexity.
Filtering techniques can have penalization-like effects influencing convexity.
Continuation methods are effective in overcoming local minima.
Abstract
Purpose: This is an attempt to better bridge the gap between the mathematical and the engineering/physical aspects of the topic. We trace the different sources of non-convexification in the context of topology optimization problems starting from domain discretization, passing through penalization for discreteness and effects of filtering methods, and end with a note on continuation methods. Design/Methodology/Approach: Starting from the global optimum of the compliance minimization problem, we employ analytical tools to investigate how intermediate density penalization affects the convexity of the problem, the potential penalization-like effects of various filtering techniques, how continuation methods can be used to approach the global optimum, and how the initial guess has some weight in determining the final optimum. Findings: The non-convexification effects of the penalization of…
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