Abstract
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.
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