A novel hybrid optimizer for solving Economic Load Dispatch problem

• We have proposed a novel hybrid DPD algorithm.
• The algorithm relies on Elitism and Non-Redundant Search.
• Its robustness was increased vastly with the help of the ‘tri-population’ mechanism to DPD.
• DPD obtains very competitive performance compared with state-of-the-art methods.
• It has better convergence rate and better efficiency.

Economic Load Dispatch (ELD) is one of the major concerns to show the potential and effectiveness of an optimization algorithm. In this context, a novel hybrid algorithm of Differential Evolution (DE) and Particle Swarm Optimization (PSO) proposed. It is based on ‘tri-population’ environment. Initially, the whole population (in increasing order of fitness) is divided into three groups –- Inferior Group, Mid Group and Superior Group. DE is employed in the inferior and superior groups, whereas PSO is used in the mid-group. The proposed method is abbreviated as DPD because it uses DE–PSO–DE on a population. Two strategies namely Elitism (to retain the best obtained values so far) and Non-Redundant Search (to improve the solution quality) have been employed in DPD cycle. Many mutation strategies of DE have emerged in the last couple of years. However, its actual ability has not been well studied yet because every mutation strategy has its own pros and cons. Therefore suitable mutation strategy for both DEs used in DPD is investigated over a set of 8 popular mutation strategies. Combination of 8 mutation strategies is generated 64 different variants of DPD. Top 4 DPDs are investigated through CEC 2006 functions out of 64 different variants of DPDs. Based on the ‘performance’ analysis best DPD is reported using CEC 2006 and 5 Engineering Design Problems. Further best DPD is considered for solving ELD problem. Results reveal that the superiority of the proposed DPD.