Modified bacterial foraging algorithm for optimum economic dispatch

This paper presents a modified bacterial foraging algorithm (MBFA) to solve the economic dispatch problem (ED) considering valve-point effects and power losses. The basic bacterial foraging algorithm (BFA) is an evolutionary optimization technique inspired by the foraging behavior of the E. coli bacteria. The original BFA has been successfully used for small scale optimization problems. On the other hand, when it is applied to larger constrained problems, it shows poor convergence characteristics. To overcome these difficulties due to the complexity and high-dimensionality of the search space of the ED problem, important modifications are introduced to enhance the performance of the BFA. A dynamic chemotactic step is proposed in order to improve the global and local search ability of the algorithm. The MBFA is tested using five case studies. Results are compared against those obtained by other algorithms previously reported in the literature.