Artificial Bee Colony Algorithm ABC Implementation

In the Artificial Bee Colony (ABC) algorithm, the main program orchestrates three distinct types of bees: employed bees, onlooker bees, and scout bees, each playing specialized roles in the optimization process. The employed bees serve as the core of the colony, responsible for exploring and discovering new food sources (solution candidates) and sharing their findings with onlooker bees through a probabilistic selection mechanism typically implemented using fitness-based roulette wheel selection. Onlooker bees then evaluate the information received from employed bees and perform local searches around promising food sources using position update equations like x_new = x_old + φ*(x_old - x_k), where φ is a random number in [-1,1] and x_k is a randomly selected neighbor solution. Scout bees monitor abandoned solutions through abandonment counters and initiate random searches in the solution space when food sources exceed predefined trial limits, ensuring diversity and preventing premature convergence. This collaborative interaction and information exchange among the three bee types enables the colony to efficiently solve optimization problems through parallel exploration-exploitation balance, rapidly converging toward optimal solutions while continuously discovering potential improvements through systematic neighborhood searches and random reinitialization strategies.