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Purpose: The literature abounds with many distinct topology optimisation methods, many of which share common parameter configurations. This study demonstrates that alternative parameter configurations may produce better results than common parameters. Additionally, we try to answer two fundamental questions: identifying the most effective topology optimisation method and determining the optimal parameter selection within this optimisation method. In order to respond to these questions, we conducted a comparative and objective analysis of topology optimisation methods. Design/methodology/approach: This paper evaluates four prominent topology optimisation methodologies, SIMP, RAMP, BESO, and LSM, based on three essential criteria: structural strength, topology quality, and computational cost. We conducted an in-depth examination of 12,500 topology optimisation results spanning a broad range of critical parameter values. These outcomes were generated using MATLAB codes. In the meantime, we comprehensively compared our findings with the existing literature on this subject. Findings: As predicted, our chosen parameters had a substantial effect on the topology quality, structural strength, and computational cost of the topology optimisation outcomes. Across the 12,500 results, many parameter combinations appeared to produce favourable results compared to conventional parameters commonly found in the existing literature. Research limitations/implications: This study focuses exclusively on four specific topology optimisation methods; however, its findings may be extrapolated to apply to other methodologies. Additionally, while it extensively examines the effects of parameters on topology quality, strength, and computational cost, it does not encompass an exploration of these parameters' impacts on other performance criteria. Originality/value: Novel parameter configurations for topology optimisation have been identified, yielding enhanced outcomes in terms of topology quality, structural strength, and computational efficiency.
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