This paper proposes a new hybrid algorithm of combining the conventional Particle Swarm Optimization (PSO) algorithm with Differential Evolution (DE) strategy, named by the authors as Particle Swarm Differential Evolution Optimization (PSDEO) to enhance better balance between local and global search abilities, while solving the economic load dispatch (ELD) problems considering all practical complex constraints and higher order non-smooth cost functions. Considering advantages and disadvantages of both the methods, PSO exploits and DE explores the search space in PSDEO more efficiently to improve the quality of solution and convergence speed. The PSDEO algorithm is tested for benchmark ELD problems, and results show an improved performance of the proposed PSDEO.

No abstract