⚡ Bolt: Optimize Pandas DataFrame iteration using itertuples/to_dict

[alinelena]

💡 What: Replaced standard Pandas df.iterrows() with df.itertuples(index=False, name=None) and df.to_dict('records') in benchmarking calculation loops across MPCONF196, solvMPCONF196, gscdb138, and elasticity.
🎯 Why: Iterating over rows with iterrows() forces Pandas to box each row into a Series object iteratively, which is extremely expensive for hundreds or thousands of rows.
📊 Impact: Expected to cut data traversal overhead dramatically (e.g. up to 10-50x faster dataframe iteration per loop).
🔬 Measurement: Verify reduction in pure iteration timing by running benchmark subsets or simply observing test suite execution times (isolated pandas parsing should be millisecond level vs second level).

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PR created automatically by Jules for task 7157959815049734537 started by @alinelena

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