AN ENHANCED JUMPING SPIDER OPTIMIZATION ALGORITHM

Abstract

Jumping Spider Optimization (JSO) algorithm is a more recent meta-heuristic algorithm shown to outperform recent algorithms in the literature. This paper presents a JSO variant that modifies standard JSO in its global search and jumping on prey phases to improve further its global search capability. The proposed algorithm employs levy flight to update the position of global search agent for better performance. It also introduces a random number generator in the equation for the trajectory of the spider when jumping on prey to provide the updated agent with flexibility to attack prey. The enhanced jumping spider optimization algorithm (EJSO) is tested on 17 well-known benchmark functions and its performance compared with the standard JSO and five other well-known algorithms. The EJSO is also verified on a welded beam design problem to validate our algorithm. The results of statistical analyses conducted show the superiority of EJSO over the standard JSO and the other state-of-arts algorithms.

Keywords

• jumping spider optimization
• bio-inspired algorithm
• meta-heuristics
• levy flight.