MATLAB Implementation of Artificial Bee Colony Algorithm with Source Code

The provided MATLAB source code offers a practical implementation of the Artificial Bee Colony optimization algorithm. The code structure enables easy customization where users can modify specific components according to their problem requirements, such as adjusting fitness functions, colony size parameters, or termination conditions. This algorithm effectively solves complex optimization challenges including path planning, machine learning parameter tuning, and engineering design problems. The implementation follows standard ABC workflow with three phases: employed bees exploring food sources, onlooker bees selecting promising solutions based on fitness values, and scout bees replacing abandoned solutions. Through deeper investigation and experimentation, users can further optimize the algorithm by enhancing neighborhood search strategies, implementing adaptive parameter control, or integrating hybrid approaches with other optimization techniques. Overall, the Artificial Bee Colony algorithm represents a potent and widely applicable optimization method with strong potential in computational intelligence applications, making it worthy of comprehensive study and practical implementation.