A Proposed Modification to the JAYA Optimization Algorithm - Application to an Abrasive Water Suspension Jet Machining Process

Abstract

Optimization plays a vital role in the application of the Industry 4.0 features in the manufacturing sector. Several optimization techniques are in use to date and immensely benefit the user. JAYA is a metaheuristic optimization method that doesn’t require any algorithm-specific parameters. This algorithm has the disadvantage of sometimes getting locked at local optima. This article offers a Modified-JAYA (ModJAYA) algorithm that incorporates the concept of ‘diversity’ into the JAYA algorithm to address the above-mentioned problem. It also hastens the entry of elite solution candidates from diverse solution space. The proposed algorithm ModJAYA is tested on two standard benchmark functions. It is then applied to an Abrasive Water Suspension Jet (AWSJ) machining process to optimize the process parameters. The effectiveness of the ModJAYA algorithm is compared with that of the JAYA algorithm and verified with that of the PSO algorithm. The ModJAYA algorithm outperformed JAYA and PSO algorithms by taking the least mean number of generations for convergence.