1. A computer-implemented method comprising: with a processor-based data importing module, importing data representing a plurality of search result sets resulting from a plurality of executed search queries, each search result set including a plurality of item listings satisfying a search query from the plurality of executed search queries and a listing slot identifier identifying a position within a search results page of a particular item listing that has resulted in a transaction being concluded, the listing slot identifier determined utilizing a production scoring function specified with one or more parameters that are weighted with a first set of one or more weighting factors; with a processor-based parameter optimization module, processing the plurality of search result sets to derive a new scoring function, the new scoring function having a second set of one or more weighting factors for one or more parameters, the second set of one or more weighting factors selected to satisfy a set of constraints, the second set of one or more weighting factors being different than the first set of one or more weighting factors, wherein the second set of one or more weighting factors are selected to maximize an average rank shift metric for the plurality of search result sets, the average rank shift metric determined by comparing the listing slot identifier as derived by the production scoring function with a listing slot identifier as derived by a new scoring function for each item listing that has resulted in a transaction being concluded for each search result set of the plurality of search result sets; and with a processor-based scoring function evaluation module, evaluating the performance of the new scoring function relative to a production scoring function.