Implementation of hybrid harmony search/random search algorithm for single area unit commitment problem

Abstract

Abstract Harmony Search (HS) is a population based metaheuristics search algorithm inspired from the musical process of searching for a perfect state of harmony and has ability to escape from local minima, does not require differential gradients and initial value setting for the variables and free from divergence and has strong ability on exploring the regions of solution space in a reasonable time. However, it has lower exploitation ability in later period and it easily trapped into local optima and converges very slowly. To improve the exploitation ability of HS algorithm in later stage and provide global optimal solution, a memetic algorithm approach considering Harmony Search and Random Search is presented in the proposed research to solve unit commitment problem of electric power system. The proposed memetic algorithm is tested for IEEE benchmarks consisting of 4, 10, 20 and 40 generating units. The effectiveness of proposed hybrid algorithm is tested for unimodal and multimodal benchmark functions and is compared with others well known evolutionary, heuristics and meta-heuristics search algorithms and it has been found that performance of proposed hybrid algorithm is much better than classical Harmony Search Algorithm and Improved Harmony Search Algorithm as well as recently developed algorithms.