Emended salp swarm algorithm for multiobjective electric power dispatch problem

Abstract

This paper presents an emended salp swarm algorithm (ESSA) which is basically the extension of the basic salp swarm algorithm (SSA) to solve multiobjective electric power load dispatch problem. The main inspiration behind ESSA is the swarming behavior and reproduction cycle of salps. Salps, in the chain, move across a multi-dimensional search space to aim for the food source (global solution). Owing to the searching behavior of SSA that makes the algorithm prone to premature convergence, the solitary and colonial reproduction phase of salp has been introduced to improve the convergence behavior along with their swarming behavior The multiobjective optimization problem is firstly converted into scalar objective exploiting fuzzy set theory and the conflicting nature of objectives is resolved by cardinal priority ranking. The variable elimination method with exterior penalty is used to handle the physical and operational constraints of generating units. The validation of the proposed ESSA has been examined on the standard benchmark functions and seven EcLD test systems including both scalar and multiple objectives. The statistical analysis based on Wilcoxon sign rank test, supports that results achieved by the algorithm are superior to the other competing algorithms. So, the proposed algorithm (ESSA) is found a promising algorithm.