Adaptive Resource Allocation in OFDM Systems Using Genetic Algorithm

When discussing adaptive resource allocation in OFDM systems, genetic algorithms represent a widely adopted optimization approach. As a heuristic optimization technique, genetic algorithms simulate natural evolutionary processes to search for optimal solutions. Our implementation provides genetic algorithm code that incorporates fundamental operations including selection, crossover, and mutation. The selection operation employs roulette wheel selection to choose chromosomes based on fitness values, while crossover uses single-point crossover to exchange genetic material between parent chromosomes. Mutation operations introduce random changes to maintain population diversity. By utilizing this genetic algorithm implementation, researchers can effectively optimize resource allocation strategies, leading to improved system performance metrics such as throughput and spectral efficiency. The code structure follows standard genetic algorithm workflow with clear separation of initialization, fitness evaluation, and evolutionary operators.