A-priori is an influential data mining algorithm employed in market basket analysis to understand the purchase
behavior of buyers. It has many other applications. In this study, we combine a-priori with a genetic algorithm (GA)
to solve two classical NP-hard location problems namely the Un-capacitated Single Allocation Problem (USAHLP)
and Un-capacitated Facility Location Problem (UFLP). A distributed model of the proposed algorithm has been
implemented. The performance of the algorithm has been evaluated with standard benchmark problems for USAHLP
and UFLP. Results have been found encouraging.