A HYBRID GENETIC ALGORITHM FOR OPTICAL ORTHOGONAL CODE CONSTRUCTION

Optical orthogonal codes (OOCs) are used to uniquely identify stations within an optical code division multiple access (CDMA) local area network (LAN). Previous efforts in constructing OOCs have focused on the use of deterministic techniques, which relied heavily on the use of Galois fields. These techniques severely restrict the availability of the resulting OOCs. This paper considers an evolutionary approach by proposing a hybrid genetic algorithm (hGA) as a flexible technique to construct OOCs. This hGA uses the simulated annealing (SA) method to generate its initial population. The effectiveness of the proposed hGA for OOC construction is demonstrated in two stages. First, we show that the SA-generated initial population is better than the randomly generated initial population in terms of fitness. Due to this, the hGA is able to converge on average two times faster compared to the use of the GA-only scheme. Second, we compare the code availability and performance of the hGA-constructed OOCs (hGA OOCs) against that of three other OOCs. Through these comparisons, we show why the proposed hGA is a more flexible technique for constructing OOCs with higher availability and better performance.