Research Area:  Metaheuristic Computing

Abstract:

In this paper, a novel hybrid lightning search algorithm-simplex method (LSA-SM) is proposed to solve the shortcomings of lightning search algorithm (LSA) premature convergence and low computational accuracy and it is applied to function optimization and constrained engineering design optimization problems. The improvement adds two major optimization strategies. Simplex method (SM) iteratively optimizes the current worst step leaders to avoid the population searching at the edge, thus improving the convergence accuracy and rate of the algorithm. Elite opposition-based learning (EOBL) increases the diversity of population to avoid the algorithm falling into local optimum. LSA-SM is tested by 18 benchmark functions and five constrained engineering design problems. The results show that LSA-SM has higher computational accuracy, faster convergence rate, and stronger stability than other algorithms and can effectively solve the problem of constrained nonlinear optimization in reality.

Keywords:  
lightning search algorithm
premature convergence
low computational accuracy
function optimization
engineering design optimization
elite opposition-based learning
stronger stability

Author(s) Name:  Hindawi

Publisher name:  Yuting Lu, Yongquan Zhou, and Xiuli Wu

DOI:  10.1155/2017/8342694

Volume Information:  Volume 2017

Paper Link:   https://www.hindawi.com/journals/ddns/2017/8342694/