A Novel Hybrid SCH-ABC Approach for the Frequency Assignment Problem

This paper proposes an efficient hybrid approach based on the stochastic competitive Hopfield neural networkSCHNN and artificial bee colony ABC, which named SCH-ABC. The hybrid algorithm aims to cope with the frequency assignment problem FAP. The objective of FAP is to minimize the cochannel interference between satellite communication systems by rearranging the frequency assignments so that they can accommodate the increasing demands. In fact, as our SCH-ABC algorithm owns good adaptability, it can not only deal with the frequency assignment problem, but also cope with other problems including the clustering, classification, the maximum clique problem etc. With the help of hybridization, SCH-ABC makes up for the defects in the Hopfield neural network and ABC while fully utilizing the advantages of the two algorithms.