Is slippage minimization even a tractable problem besides applying loose heuristics derived from empirical insights, e.g., identifying reliable early-signals of narrowing spreads and increased liquidity for a given exchange?
It doesn’t require very advanced modeling to estimate a probability of e.g. getting filled at midprice (saving half the bid/ask spread) within a short time period.
Just basic Bayesian with a look-back window.
Execution cost is a big topic in the trading industry.