Solving Environmental/economic Dispatch Problem Using an Improved Multiobjective Scatter Search Approach

The environmental/economic dispatch (EED) problem is a large-scale highly constrained nonlinear multiobjective optimization problem. In recent years, this option has received much attention. Many approaches and methods have been reported to solve the multiobjective EED problem in the literature, such as genetic algorithms, artificial neural networks, particle swarm optimization, and differential evolution. In terms of metaheuristics, recently, scatter search approaches are receiving increasing attention, because of their potential to effectively explore a wide range of complex optimization problems. Scatter search is an evolutionary method that shares with genetic algorithms, the employment of a combination method that combines the features of two parent vectors to form several offspring. It generates a reference set from a population of solutions. Then the solutions in this reference set are combined to get starting solutions to run an improvement procedure, whose result may indicate an updating of the reference set and even an updating of the population of solutions. Furthermore, an important aspect concerning scatter search is the trade-off between the exploration abilities of the combination method and the exploitation capacity of the improvement mechanism. In this paper, we deal with a continuous version of the scatter search algorithm, which works directly with vectors of real components to solve multiobjective EED problems. In the proposed work, we have considered the standard IEEE (Institute of Electrical and Electronics Engineers) 30-bus with six-generators test system and the results obtained by proposed algorithm are compared with the other recently reported results in the literature. Simulation results demonstrate that the proposed improved scatter search algorithm is a capable candidate in solving the multiobjective EED problems. In addition, a quality measure to Pareto-optimal solutions has been implemented where the results corroborate the potential of the proposed improved scatter search technique to solve the multiobjective EED problem and produce high quality nondominated solutions.