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Despite its strengths, MVO often encounters limitations due to premature convergence, reducing its overall efficiency. To combat this, the study introduces an enhanced version of MVO, termed the improved MVO (iMVO), which incorporates an opposition\u2010based learning (OBL) strategy to overcome this limitation. The effectiveness of iMVO is assessed through a series of tests involving both classical and IEEE CEC 2021 benchmark functions, demonstrating competitive performance against established algorithms. Moreover, the applicability of iMVO to real\u2010world challenges is validated through its successful deployment in civil engineering tasks, particularly in optimizing truss designs and managing time\u2010cost tradeoffs. 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