Oppositional Real Coded Chemical Reaction Optimization for different economic dispatch problems

This paper proposes an effective oppositional Real Coded Chemical Reaction algorithm (ORCCRO) to solve Economic Load Dispatch (ELD) problems involving different equality and inequality constraints. Effects of valve-point loading, multi-fuel options of large-scale thermal plants are also studied. System transmission loss has also been considered in few cases. Chemical Reaction Optimization (CRO) imitates the interaction of molecules in a chemical reaction to reach from a higher energy unstable state to a low energy stable state. A real coded version of it, known as Real-coded chemical reaction optimization (RCCRO). Oppositional based RCCRO (ORCCRO) have been used here to improve the effectiveness and quality of solutions in minimum time. The proposed opposition-based RCCRO (ORCCRO) of the present work employs opposition-based learning for population initialization and also for generation wise update operation. In the present work, quasi-opposite numbers have been utilized instead of pseudo random numbers to improve the convergence rate of the RCCRO. Simulation results establish that the proposed approach outperforms several other existing optimization techniques in terms quality of solution obtained and computational efficiency. Results also prove the robustness of the proposed methodology to solve ELD problems.