A Hybrid Algorithm Based on Artificial Bee Colony and Artificial Rabbits Optimization for Solving Economic Dispatch Problem

The Artificial Bee Colony (ABC) algorithm has gained widespread attention and has been applied in various fields due to its ability to achieve excellent global optimization results and ease of implementation. Despite these advantages, the basic ABC algorithm has some drawbacks such as slow convergence, poor exploitation, and difficulty in finding the best solution among all feasible solutions in some cases. Hence, a hybrid optimization algorithm called Artificial Bee Rabbit Optimization (ABRO) is proposed in this paper. This algorithm synergizes the ABC algorithm and Artificial Rabbits Optimization (ARO) algorithm. The original ABC algorithm has a better exploration approach while the ARO algorithm has a better exploitation strategy when approaching the optimum value. The new hybrid algorithm integrates the good features of both standard optimization strategies, thus producing better possible solutions. Four types of benchmark functions are applied to test the performances of the proposed algorithm. Furthermore, the proposed algorithm is applied in the IEEE-26 bus system for tackling the economic dispatch problem. The results show that the ABRO algorithm outperforms the original ABC algorithm and ARO algorithm in all benchmark functions and successfully reduces the cost of the power generation for the IEEE- 26 bus system.