Interior Search Algorithm (IS A) is a novel algorithm recently developed for solving optimization problems. Though, this metaheuristic has proven to be effective for function optimization on widely used benchmark functions, this algorithm may converge slowly or be trapped in local minima for complex functions. In this paper, a new hybrid approach of IS A is presented. The proposed approach includes a fuzzy logic system for improving convergence of the solutions in IS A by dynamic parameter adaptation. To validate the performance of the proposed algorithm, several comparisons are presented on the basis of benchmark functions. Simulation results demonstrated the efficiency of the proposed fuzzy IS A algorithm.

Economic load dispatch is an area of serious attention for reducing the final cost of electric power consumption. Generator rescheduling is done by optimal allocation of generating units to obtain a better effective and economic load dispatch. This paper uses a Newton Raphson technique to obtain optimal power flow for load flow analysis and Particle swarm optimization technique is used to find the optimal generator rescheduling. The proposed technique is tested on standard IEEE 14 bus system. The minimum fuel cost concurred under this technique is the parameter which determines the fitness of the function.